Electrical Engineering, Computer Engineering and Informatics

PhD posts, starting September 2019

The last date to apply for postgraduate studies is Tuesday 30 April 2019.

For applications, click  here

 

  • One (1) post in the following topic: “Machine Learning Methodologies for Gravitational Waves Modeling”

Description: The goal of this doctoral thesis position is to examine and devise novel and effective machine learning methodologies, especially deep learning, for successfully modeling gravitational waves. We particularly focus on gravitational wave denoising via unsupervised latent variable modeling, as well as real-time gravitational wave detection and characterization. The completion of this thesis will be facilitated by the close collaboration with the European Gravitational Observatory (EGO); this world-leading institute will indicate the datasets we will employ, as well as the benchmarks used for comparison and method evaluation.

The ideal candidate must have some affinity with statistical modeling, especially in the context of deep learning, as well as the Python programming language. No need of advanced physics is required.

Research Advisors:  Sotiris Chatzis, Assistant Professor, sotirios.chatzis@cut.ac.cy

 

  • One (1) post in the following topic: “Complex Networks: Geometry, Dynamics and Prediction”

Description: Real-world complex networked systems (technological, biological, social, financial, etc.) can be mapped to geometric spaces that lie hidden beneath their observable topologies. These geometric spaces are called “hidden”, as they play the role of an underlying coordinate system, not readily observable by examining the network topology. Nodes closer in the underlying space are connected in the observable network topology with higher probability.

The PhD candidate will focus in studying the properties of these underlying geometric spaces and the spatial dynamics of network nodes in these spaces. It is anticipated that important fundamental and practical questions will be addressed through this PhD thesis such as: (i) what are the laws governing the “motion” of network nodes in these spaces? (ii) Can this motion be modeled using classical mechanics laws, e.g., Newton’s laws of motion or stochastic versions of it? (Iii) is this motion chaotic or can be predicted? (iv) Given that we can predict this motion, can we predict the future structure and evolution of real complex networks?

This position falls under the general scientific areas of Network Science, Data Science, and Predictive Analytics. The ideal candidate should like networks. He/she should also like mathematics and probability, and should have excellent computer programming skills.

Research Advisor: Fragkiskos Papadopoulos, Assistant Professor, f.papadopoulos@eecei.cut.ac.cy

 

  • One (1) post in the following topic:  “Geometric Analysis and Dynamics of Brain Networks”

Description: Mapping the structural and functional connections of the human brain is one of the great scientific challenges of the 21st century, and real data with unprecedented resolution in space and time are being made publicly available for the first time (http://www.humanconnectome.org/). In this context, a great deal of recent research studies brain dynamics; the dynamics of the functional brain connectivity, i.e., the functional connections and disconnections taking place in the brain, at rest, during various tasks, or during abnormal behaviors, such as epileptic seizures. Furthermore, it has been recently recognized that the brain’s structural and functional systems have features common to other complex networks found in nature and society.

The PhD candidate will focus on: (i) data extraction and graph-theoretic analysis of brain network data from the human connectome project; (ii) mapping of these network data into different geometric spaces; (iii) studying the spatial dynamics of network nodes in these spaces; (iv) identifying laws/processes that can potentially describe these spatial dynamics; and (v) use the discovered laws to predict brain network dynamics.

This position falls under the general scientific areas of Network Science, Data Science, Brain Science, and Predictive Analytics. The ideal candidate should like networks. He/she should also like mathematics (especially statistics), and aspects of neuroscience. He should also have excellent computer programming skills. The research will take place in collaboration with researchers from the Department of Bioengineering at McGill University, Canada.

Research Advisor: Fragkiskos Papadopoulos, Assistant Professor, f.papadopoulos@eecei.cut.ac.cy

 

  • One (1) post in the following topic:  “Evaluation of a Magnetic Resonance Imaging (MRI) Guided Focused Ultrasound System for Ablation in the Abdominal Area”

Description: Focused ultrasound is a modality that can be used to treat various diseases in the area of oncology using thermal protocols. The thermal effects of Focused ultrasound can be monitored with excellent contrast using Magnetic resonance imaging (MRI).

The offered position will concentrate on the evaluation of an existing 4-D MR compatible robotic system. A major task is to design an agar-based prostate phantom.  Simulations will be performed in order to optimize the focused ultrasound therapeutic protocols.  A transducer design dedicated for ablation in the abdominal area will be performed.  The successful applicant is expected to extensively evaluate the system in the developed phantom in the laboratory setting and inside an MRI scanner.  MRI sequences will be optimized in order to monitor the thermal effects of ultrasound.

Required qualifications: MSc in Electrical Engineering, or Mechanical Engineering, or Physics.

Research Advisor: Christakis Damianou, Professor, christakis.damianou@cut.ac.cy

 

  • One (1) post in the following field: “Resilient Wear-Aware Computer Architectures”

Description: Moore’s Law scaling continues to yield higher transistor density with each succeeding process generation, leading to today’s many-core chip multiprocessors (CMPs) with tens of interconnected cores or tiles. Unfortunately, deep submicron CMOS process technology is marred by increasing susceptibility to wear. Prolonged operational stress gives rise to accelerated wear out and failure due to several physical failure mechanisms. Unfortunately, such wear can prove catastrophic to the reliable operation of CMPs, as various chip components may introduce errors and/or cause timing violations during computation and data transportation across the chip, deeming it inoperable.

To avoid such detrimental effects this research topic will deal with the development of wear out-decelerating techniques so as to slow-down wear in CMP components and improve their resilience, including their processors, memory, and on-chip interconnect. Such techniques will be incorporated seamlessly into the existing CMP architecture to work online during chip operation. Since wear in CMOS transistors is workload-related, a key drive of this research topic will be to understand the usage patterns of applications over time so as to adopt appropriate wear-aware policies to them toward maximally extending their lifetime. As such, wear-aware policies may be based on artificial neutral network techniques or algorithms which are very good in recognizing patterns and adapting to them. Other pattern recognition schemes will also be examined to further explore the design space of wear-reducing architectural-level policies. Wear-aware hardware augmentations to the base CMP architecture will be implemented using hardware description languages (e.g., VHDL) to prove their feasibility.

Required Qualifications: Candidates should possess a Master’s-level degree in the field of Computer Science, or Computer Engineering, or Electrical Engineering. This research position falls under the themes of computer architecture, distributed computer systems, interconnection/computer networks, artificial neural network architectures, algorithms, computer programming in C/C++, hardware-description languages (such as VHDL or Verilog) and circuit synthesis, and to some extent mathematics.

Research Advisor:  Vassos Soteriou, Associate Professor, vassos.soteriou@cut.ac.cy

 

  • One (1) post in the following field: “Design of Hardware-Level-Secure and Trustful Multi-Core Processors and their Networks-on-Chips (No’s)”

Description: Today our modern societies rely more and more on information technology (IT), in which trustworthiness, reliability and secure information handling have become key expectations and requirements. Despite this, various malicious parties have repeatedly attempted to steal and manipulate user data so as to cause damage, source quick and unlawful financial gain, and steal sensitive information such as user identities and military/corporate secrets, etc. Until recently, these parties have focused on the software components of computers to gain access to such sensitive information, however recently; unfortunately the computer hardware itself has been misused and tampered so as to gain access to such info. These parties make use of various hardware vulnerabilities that either resides in the existing integrated circuit production chain, or directly within the processor hardware and its design.

This research topic will investigate and develop various techniques to empower the “design of processor and interconnect circuits for trust” so as to effectively protect and secure personal data within the computing hardware itself. It will focus on leveraging recent advances seen in multi-core processors and their contained on-chip interconnects so as to lock, or render the underlying digital electronics unusable, should a malicious entity attempt to steal, compromise, misuse or tamper with a physical processor. As such, dedicated physical features will be researched, developed and incorporated into existing off-the-shelf processor designs (such as the ARM M0+ microcontroller as a base) to showcase robust and resilient protection of personal data at the hardware level.

Required Qualifications: Candidates should possess a Bachelor’s Degree, preferably a Master’s-level postgraduate degree, in either the field of Computer Science, or Computer Engineering, or Electrical Engineering. This research position falls under the themes of computer architecture, distributed systems, interconnection/computer networks, security algorithms, computer programming in C/C++, the usage of hardware-description languages (such as VHDL or Verilog), and to some extent mathematics.

Research Advisor:  Vassos Soteriou, Associate Professor, vassos.soteriou@cut.ac.cy

 

  • One (1) position in the following field: “Mathematical modeling and performance analysis of micro-network router architectures and traffic flows”

Description: This research topic concentrates on elaborate detailed mathematical models to capture in detail the behavior of the architecture of pipelined micro-routers utilized in micro-interconnect networks found in today’s multi-core processors and embedded systems. Various state-of-the-art architectures will be considered. The interaction of the underlying router organization will be considered in tandem with various flow-control protocols and routing algorithms, along with numerous traffic flow spatio-temporal behaviors in order to determine throughput and network latency levels that will act as indicators of architectural router performance. Results obtained from software simulations of equivalent architectures will be carried out to confirm the validity and the accuracy of the mathematically-modeled micro-router architectures.

Required Qualifications: Candidates should possess a Bachelor’s Degree and a Master’s-level postgraduate degree from accredited universities in the field of Computer Science, or Electrical Engineering, or Computer Engineering or Mathematics with a preferred specialization in computer architecture, computer networks, discrete mathematics, statistics, or related.  The candidate should have 2+ years of experience in object-oriented programming and be fluent in C++ programming and/or Python. A strong mathematical background is desired. Excellent command of the English language is a must.

Research Advisors:  

Vassos Soteriou, Associate Professor, vassos.soteriou@cut.ac.cy

Paul Christodoulides, Assistant Professor, paul.christodoulides@cut.ac.cy

 

  • Four (4) Posts  in any of the following subjects:

“Automated Software Testing”

Description: Methods, techniques, models and algorithms for performing software testing in an automated way, with little or no human intervention. Use of Computational Intelligence or/and of other sub-areas of Computer Science for performing black-box (specifications-based) and glass-box (source code-based) testing for classic software systems, web applications and mobile software.

Required qualifications: BSc and/or MSc in Computer Science or Computer Engineering or Informatics or any other related field. Prior experience or specialization (i.e. during BSc or MSc in Software Engineering) will be considered as advantage.

«Smart Manufacturing – Industry 4.0»

Description: Smart Manufacturing is a term coined by several agencies like the Department of Energy (DoE) and the National Institute of Standards and Technology (NIST) in the United States. Smart Manufacturing is described in short as “a data intensive application of information technology at the shop floor level and above to enable intelligent, efficient and responsive operations”. There are multiple more comprehensive definitions available and they all highlight the use of Information and Communication Technology (ICT) and advanced data analytics to improve manufacturing operations at all levels of the supply network, be it the shop floor, factory, or Supply Chain. The fourth industrial revolution is characterized by the introduction of the Internet of things (IoT) and Internet of services concepts into manufacturing, which enables smart factories with vertically and horizontally integrated production systems. In industries worldwide, highly flexible processes that can be changed quickly enable individualized mass production. Variants are self-determined through items delivering their own production data to intelligent machines, which are aware of the environment, exchange information, and control processes in production and logistics by themselves. Data are collected along the entire life cycle in large quantities and stored decentralized to enable local decisions; however, the said data are still transparent to be exchanged with partners. In order to realize this vision, elements such as machines, storage systems, and utilities must be able to share information, as well as act and control each other autonomously. Such systems are called cyber-physical systems (CPS). The research to be conducted will revolve around the aforementioned concepts and will utilize forms of smart data processing, visualization & analytics, IoT, CPS and production line automations through sensing and actuating. This topic will be investigated with the support of local industrial collaborators (Muskita, Paradeisiotis) that will offer a real-world environment (and data) for experimentation and validation.

Required qualifications: BSc and/or MSc in Computer Science or Computer Engineering or Informatics or any other related field. Prior experience or specialization (i.e. during BSc or MSc in Software Engineering) or any involvement with research in the past will be considered as advantage.

«Automatic Resource Management for the Cloud»

Description: This research topic will concentrate on algorithms, methods and techniques for automating certain process in the Cloud environment dealing with how resources are managed. More specifically, Computational Intelligence – CI approaches will be utilized to tackle issues and solve problems related to optimizing the way resources are managed (e.g. physical servers, virtual machines, etc.) in such a way so that clients are serviced according to their Service Level Agreements – SLA, with high quality and performance, but at the same time energy and cost preservation is taken into consideration. Fog computing will also be investigated as the paradigm that pushes processing intelligence and data down to the local area network level of network architecture and a fog node to avoid latencies.

In this context different CI models will be investigated and apply in single- and multi-objective optimization of Cloud resources.

Required qualifications: BSc and/or MSc in Computer Science or Computer Engineering or Informatics or any other related field. Prior experience or specialization (i.e. during BSc or MSc in Software Engineering) or any involvement with research in the past will be considered as advantage.

"Software Engineering and Intelligent Data Processing in Distributed Block chain Processing Systems"

Research will focus on methodologies and techniques for the development of software systems for distributed processing in the new computational model of Blockchain. Particular emphasis will be placed on the automation of smart data processes in this environment, using models and algorithms of Computational and Artificial Intelligence, as well as single and multi-objective optimization methods. This subject will apply research results to real-world systems that are already running or are going to be developed in the Block chain environment, mainly from the Financial Sector, and may be supported by local private organizations by means of data provision and/or funding (currently in discussions with positive reactions).

Required qualifications: BSc and/or MSc in Computer Science or Computer Engineering or Informatics or any other related field. Prior experience or specialization (i.e. during BSc or MSc) in Software Engineering and/or Computational or Artificial Intelligence, or any involvement with research in the past will be considered as advantage.

Research Advisor: Andreas S. Andreou, Professor, andreas.andreou@cut.ac.cy

 

  • One (1) post in the following field: “Event Detection, Localization and Tracking using Wireless Sensor Networks”

Description: Wireless Sensor Networks (WSNs) are a fairly new technology that can potentially provide an interface between the physical world and computers allowing the latter to vanish into the background. They have a wide variety of applications including military sensing, infrastructure security, environment and habitat monitoring, industrial sensing, building and structure monitoring, and traffic control.  The proposed research is expected to be based on ideas and techniques from a variety of different fields including Wireless Communication Systems, Computer Networks, Collaborative Signal and Information Processing and Computational Intelligence. The offered positions will concentrate on the development of new algorithms and techniques for detecting, localizing and tracking an event. The developed algorithms should feature low computational complexity, distributed implementation and fault tolerance in order to address the limitations of WSNs in terms of energy and bandwidth and the harsh conditions of operation. The successful applicants are expected to perform real–time experiments in order to verify the performance of their algorithms using the WSN platform at the Cyprus University of Technology.    

Required qualifications: BSc (required) and MSc (preferably) in Electrical Engineering and/or Computer Science. Prior research experience or specialization in related topics will be considered an advantage.

Research Advisor: Michalis Michaelides, Assistant Professor,   michalis.michaelides@cut.ac.cy

 

  • One (1) position in the following field: “Contaminant Event Monitoring in Intelligent Buildings”

Description: An Intelligent Building is a system that incorporates computer technology to autonomously govern and adapt the building environment in order to enhance operational and energy efficiency, cost effectiveness, improve user’s comfort, productivity and safety, and increase system robustness and reliability. The dispersion of contaminants from sources (events) inside a building can compromise the indoor air quality and influence the occupants' comfort, health, productivity and safety. These events could be the result of an accident, faulty equipment or a planned attack. Under these safety-critical conditions, immediate event detection should be guaranteed and the proper actions should be taken to ensure the safety of the people. The proposed research will investigate and produce solutions for the problem of monitoring the indoor building environment against the presence of contaminant events.  Distributed sensor networks have been widely used in buildings to monitor indoor environmental conditions such as air temperature, humidity and contaminant concentrations (e.g. CO, CO2). The goal of this research will be the development of methods for interpreting the real-time-collected data coming from the sensors in order to ensure the accurate and prompt identification of contaminant sources. The results can help determine appropriate control solutions such as: (i) indicating safe rescue pathways and/or refugee spaces, (ii) isolating contaminated spaces and (iii) cleaning contaminant spaces by removing sources, ventilating and filtering air.  

Required qualifications: BSc (required) and MSc (preferably) in Electrical Engineering and/or Computer Science. Prior research experience or specialization in related topics will be considered an advantage.

Research Advisor: Michalis Michaelides, Assistant Professor,   michalis.michaelides@cut.ac.cy

 

  • One (1) position in the following field: Air Quality Monitoring in Smart Cities using Wireless Sensor Networks

Description: Currently, there is a lack of sufficient infrastructure for environmental monitoring, both spatially (in multiple points) and temporally (in regular time intervals). The proposed wireless sensor network can constitute an economical and reliable solution to the problem of sufficient monitoring and control of the city air quality. The proposed research will focus on the development of innovative algorithms and techniques for detecting, identifying and tracking the release of pollutants in an urban environment using a wireless sensor network. More specifically, the successful candidate is expected to use signal processing and machine learning methods to analyze the collected data from the sensors in order to: (i) construct a fine-grained pollution map of the city, (ii) identify the main sources of pollution and estimate their locations, (iii) develop models for predicting the pollution levels in the near future. These results are expected to provide the necessary information for reducing the pollution levels through appropriate actions and policies, leading to a cleaner and safer city environment.  The successful applicants are expected to work with real data in order to verify the performance of their algorithms using the established WSN platform at the Cyprus University of Technology.

Required qualifications: BSc (required) and MSc (preferably) in Electrical Engineering and/or Computer Science. Prior research experience or specialization in related topics will be considered an advantage.

Research Advisors: Michalis Michaelides, Assistant Professor,   michalis.michaelides@cut.ac.cy

 

  • One (1) post in the following field: “Information and Communication Systems for Smart Ports”

Description: Ports have played a crucial role in connecting the Europe markets with island areas, such as Cyprus, as 74% of goods imported or exported from Europe travel through sea transport. The application of new information and communication systems and technologies can significantly improve the efficiency of the various port operations and services via enabling real-time situation awareness to all participants involved in maritime activities in the ports of Cyprus. The proposed research will investigate the implementation of such systems at the Port of Limassol for collecting real-time information related to ship movements, the environment, and the tracking of cargo by exploiting innovative technological solutions such as buoys, UAVs, and RFIDs. The collected information, will be further processed using advanced data analytics for ensuring high quality data, calculating KPIs, and creating new decision-support tools and services for maritime stakeholders. The successful applicants are expected to perform real–time experiments in order to verify the performance of the developed algorithms and solutions using the implemented systems at the Port of Limassol.     

Required qualifications: BSc (required) and MSc (preferably) in Electrical Engineering, or Computer Science, or related field. Prior research experience or specialization in related topics will be considered an advantage.

Funding: Funding is available for full-time qualified applicants through involvement in a nationally-funded Research Program.

Research Advisors:

Michalis Michaelides, Assistant Professor,   michalis.michaelides@cut.ac.cy

Herodotos Herodotou Assistant Professor, herodotos.herodotou@cut.ac.cy

 

  • One (1) post in the following topic: “Development of Optical Fiber Plasmonic Sensors and Nanoantennas Using Femtosecond Laser Pulses”

Required Qualifications:  BSc and/or MSc in Electrical Engineering or Physics, or any other related subject. Strong mathematical background will be considered an advantage.

The PhD will focus on the development of photonic (bio)chemical sensing platforms, using custom sensors developed in-house with a femtosecond laser system. The PhD will focus on tilted fibre Bragg gratings surrounded by nanoscale coatings of metal layers and nanoparticles that will be studied and optimized to exploit the plasmonic enhancement of the sensing transduction mechanisms.

Research Advisors:   Kyriacos Kalli, Professor, kyriacos.kalli@cut.ac.cy

 

  • One (1) post in the following topic:  “Optical Fibre Sensors for Biomedical Applications”

Required Qualifications: BSc and/or MSc in Electrical Engineering or Physics, or any other related subject. Strong mathematical background will be considered an advantage.

Research Advisors:   Kyriacos Kalli, Professor, kyriacos.kalli@cut.ac.cy

 

  • One (1) post in the following topic: IdeNtity verifiCatiOn with privacy-preservinG credeNtIals for anonymous access To Online services

The main purpose of INCOGNITO project is to develop a user-friendly authentication system that offers secure digital identity, privacy, and anonymity through the use of anonymous credentials. The program aims at designing and implementing an infrastructure that supports the anonymity of the user by using cryptographic anonymous credentials as well as Federated Login solutions. Also, this system, which can be a central entity, or distributed using blockchain, enables the user to consolidate, manage, and verify their identity safely by using physical identity documents and online accounts on the Internet.

The INCOGNITO consortium includes the Telecommunication operator Telefonica, the certSIGN computer security provider, the University of Piraeus, and small and medium-sized technology companies from Spain and Greece. The ultimate goalof the program is to evaluate the aforementioned technologies by end-users. More information on the work already done in this area by CUT can be found at the web site of the ReCRED (https://www.recred.eu/) research project, which has recently ended. CUT was the technical manager of ReCRED.

CUT’s main research fields in the CONCORDIA project are divided in three main pillars:

Privacy: The protection of user personal data on the web and the detection of personal data leakages to unauthorized parties, mainly the ad-ecosystem. The research around this field aims to result to tools able to detect such user data leakages. In addition, methods should be proposed to tackle such problems, based on advanced machine learning and deep learning techniques.

Identity management: This part focuses on the management, authentication and verification of users’ identity on Online Social Networks (OSN). The researcher assigned to tackle this problem will research and acquire blockchain knowledge since a blockchain-based identity verification and management ecosystem is aimed to be built in order to allow users to consolidate, authenticate and verify their real-world identities without the need to trust a centralized authority for storing and managing their personal information.

Cybersafety / Fake News: This part studies the detection of accounts (trolls/fake accounts) that disseminate disinformation on OSN. At the same time, it focuses on the analysis and detection of this information using advanced, innovative machine learning detection techniques.

In the CONCORDIA project participate big names in the areas of telecommunication namely, Telefonica and TELECOM Italia. In addition many well-known companies and organizations are part of the consortium, like AIRBUS, BMW, Siemens, and Caixa Bank. Also, distinctly recognized universities of Germany, Italia, Slovenia, Greece, England, Check Republic, Israel, Norway, Slovenia, Belgium, Holland, Luxemburg and France participate in this project.

More information on the work already done in this area by CUT can be found at the web site of ENCASE (https://encase.socialcomputing.eu/) research project. CUT is the Coordinator of ENCASE.

The Cyprus University of Technology participates in the above program with the NetSySci Lab (https://netsysci.cut.ac.cy/) under the umbrella of the Social Informatics Research Center (https://www.socialcomputing.eu/).

The PhD student will acquire, through studies and research, expertise in Networked Systems, Security, Cybersafety and Large Scale Data Processing. He/she will be called to research and develop methods for large scale extraction of Online Social Network (OSN) information and perform analysis on that data.

The successful applicants should be able to demonstrate excellent knowledge of CS theory as well as outstanding software implementation skills.

Required Qualifications:              

  • BSc or MSc from a recognized university in Electrical Engineering or Computer Science.
  • Programming experience in a high-level programming language
  • Very good knowledge of English (spoken and written).
  • Organizational skills.
  • Participation in funded research programs will be considered as an additional qualification
  • Prior research experience or specialization in Computer Security will be considered an advantage.

Funding prospects: The selected candidate will be funded by the European Commission’s Horizon 2020 framework program.

Research Advisor: Michael Sirivianos, Associate Professor, michael.sirivianos@cut.ac.cy.

 

  • One (1) post in the following topic: Α Security ECONomics service platform for smart security investments and cyber insurance pricing in the beyonD 2020 netwOrking era”

The main purpose of the SECONDO project is to optimize decisions on cyber-security investments and insurance pricing. Simply put, the program aims to support professionals seeking investment in cyber security. It is a top-of-the-line research problem, as the rapid development of cyber-attacks is expected to continue its upward course.

SECONDO therefore proposes a unique, scalable, highly interoperable platform that encompasses a comprehensive cost-driven methodology for: (i) estimating cyber risks based on a quantitative approach that focuses on both technical and non-technical aspects, (e.g. users behaviour), that influence cyber exposure; (ii) providing analysis for effective and efficient risk management by recommending optimal investments in cyber security controls; and (iii) determining the residual risks and estimating the cyber insurance premiums taking into account the insurer’s business strategy, while eliminating the information asymmetry between the insured and insurer.

The aim of the SECONDO PhD researcher position is to combine statistical and technical knowledge to develop innovative cyber-security software and algorithms that will help users make decisions about investment, risk assessment, and pricing of insurance.

The SECONDO project involves the University of Piraeus and Surrey, as well as small and medium-sized technology and research companies from Cyprus, Greece and Spain.

The Cyprus University of Technology participates in the above program with the NetSySci Lab (https://netsysci.cut.ac.cy/) under the umbrella of the Social Informatics Research Center (https://www.socialcomputing.eu/).

The successful applicants should be able to demonstrate excellent knowledge of CS theory as well as outstanding software implementation skills.

Required Qualifications:              

  • BSc or MSc from a recognized university in Electrical Engineering or Computer Science.
  • Programming experience in a high-level programming language
  • Very good knowledge of English (spoken and written).
  • Organizational skills.
  • Participation in funded research programs will be considered as an additional qualification
  • Prior research experience or specialization in Computer Security will be considered an advantage.

Funding prospects: The selected candidate will be funded by the European Commission’s Horizon 2020 framework program.

Research Advisor: Michael Sirivianos, Associate Professor, michael.sirivianos@cut.ac.cy.

 

  • One (1) post in the following topic:  “Night Cooling Systems: Modeling and monitoring systems”
  • Or one (1) post in the following topic:  “Theoretical and Experimental investigation of geothermal systems”

Required Qualifications:  BSc and/or MSc in Electrical Engineering and Computer Engineering or Computer Science or Physics, or any other related subject. Strong mathematical modeling background will be considered an advantage.

Research Advisor:  Paul Christodoulides, Assistant Professor, paul.christodoulides@cut.ac.cy

 

Information:

Department Secretary

Tel: 25002533, Fax: 25002635

 

Electrical Engineering, Computer Engineering and Informatics

PhD posts, starting September 2019

The last date to apply for postgraduate studies is Tuesday 30 April 2019.

For applications, click  here

 

  • One (1) post in the following topic: “Machine Learning Methodologies for Gravitational Waves Modeling”

Description: The goal of this doctoral thesis position is to examine and devise novel and effective machine learning methodologies, especially deep learning, for successfully modeling gravitational waves. We particularly focus on gravitational wave denoising via unsupervised latent variable modeling, as well as real-time gravitational wave detection and characterization. The completion of this thesis will be facilitated by the close collaboration with the European Gravitational Observatory (EGO); this world-leading institute will indicate the datasets we will employ, as well as the benchmarks used for comparison and method evaluation.

The ideal candidate must have some affinity with statistical modeling, especially in the context of deep learning, as well as the Python programming language. No need of advanced physics is required.

Research Advisors:  Sotiris Chatzis, Assistant Professor, sotirios.chatzis@cut.ac.cy

 

  • One (1) post in the following topic: “Complex Networks: Geometry, Dynamics and Prediction”

Description: Real-world complex networked systems (technological, biological, social, financial, etc.) can be mapped to geometric spaces that lie hidden beneath their observable topologies. These geometric spaces are called “hidden”, as they play the role of an underlying coordinate system, not readily observable by examining the network topology. Nodes closer in the underlying space are connected in the observable network topology with higher probability.

The PhD candidate will focus in studying the properties of these underlying geometric spaces and the spatial dynamics of network nodes in these spaces. It is anticipated that important fundamental and practical questions will be addressed through this PhD thesis such as: (i) what are the laws governing the “motion” of network nodes in these spaces? (ii) Can this motion be modeled using classical mechanics laws, e.g., Newton’s laws of motion or stochastic versions of it? (Iii) is this motion chaotic or can be predicted? (iv) Given that we can predict this motion, can we predict the future structure and evolution of real complex networks?

This position falls under the general scientific areas of Network Science, Data Science, and Predictive Analytics. The ideal candidate should like networks. He/she should also like mathematics and probability, and should have excellent computer programming skills.

Research Advisor: Fragkiskos Papadopoulos, Assistant Professor, f.papadopoulos@eecei.cut.ac.cy

 

  • One (1) post in the following topic:  “Geometric Analysis and Dynamics of Brain Networks”

Description: Mapping the structural and functional connections of the human brain is one of the great scientific challenges of the 21st century, and real data with unprecedented resolution in space and time are being made publicly available for the first time (http://www.humanconnectome.org/). In this context, a great deal of recent research studies brain dynamics; the dynamics of the functional brain connectivity, i.e., the functional connections and disconnections taking place in the brain, at rest, during various tasks, or during abnormal behaviors, such as epileptic seizures. Furthermore, it has been recently recognized that the brain’s structural and functional systems have features common to other complex networks found in nature and society.

The PhD candidate will focus on: (i) data extraction and graph-theoretic analysis of brain network data from the human connectome project; (ii) mapping of these network data into different geometric spaces; (iii) studying the spatial dynamics of network nodes in these spaces; (iv) identifying laws/processes that can potentially describe these spatial dynamics; and (v) use the discovered laws to predict brain network dynamics.

This position falls under the general scientific areas of Network Science, Data Science, Brain Science, and Predictive Analytics. The ideal candidate should like networks. He/she should also like mathematics (especially statistics), and aspects of neuroscience. He should also have excellent computer programming skills. The research will take place in collaboration with researchers from the Department of Bioengineering at McGill University, Canada.

Research Advisor: Fragkiskos Papadopoulos, Assistant Professor, f.papadopoulos@eecei.cut.ac.cy

 

  • One (1) post in the following topic:  “Evaluation of a Magnetic Resonance Imaging (MRI) Guided Focused Ultrasound System for Ablation in the Abdominal Area”

Description: Focused ultrasound is a modality that can be used to treat various diseases in the area of oncology using thermal protocols. The thermal effects of Focused ultrasound can be monitored with excellent contrast using Magnetic resonance imaging (MRI).

The offered position will concentrate on the evaluation of an existing 4-D MR compatible robotic system. A major task is to design an agar-based prostate phantom.  Simulations will be performed in order to optimize the focused ultrasound therapeutic protocols.  A transducer design dedicated for ablation in the abdominal area will be performed.  The successful applicant is expected to extensively evaluate the system in the developed phantom in the laboratory setting and inside an MRI scanner.  MRI sequences will be optimized in order to monitor the thermal effects of ultrasound.

Required qualifications: MSc in Electrical Engineering, or Mechanical Engineering, or Physics.

Research Advisor: Christakis Damianou, Professor, christakis.damianou@cut.ac.cy

 

  • One (1) post in the following field: “Resilient Wear-Aware Computer Architectures”

Description: Moore’s Law scaling continues to yield higher transistor density with each succeeding process generation, leading to today’s many-core chip multiprocessors (CMPs) with tens of interconnected cores or tiles. Unfortunately, deep submicron CMOS process technology is marred by increasing susceptibility to wear. Prolonged operational stress gives rise to accelerated wear out and failure due to several physical failure mechanisms. Unfortunately, such wear can prove catastrophic to the reliable operation of CMPs, as various chip components may introduce errors and/or cause timing violations during computation and data transportation across the chip, deeming it inoperable.

To avoid such detrimental effects this research topic will deal with the development of wear out-decelerating techniques so as to slow-down wear in CMP components and improve their resilience, including their processors, memory, and on-chip interconnect. Such techniques will be incorporated seamlessly into the existing CMP architecture to work online during chip operation. Since wear in CMOS transistors is workload-related, a key drive of this research topic will be to understand the usage patterns of applications over time so as to adopt appropriate wear-aware policies to them toward maximally extending their lifetime. As such, wear-aware policies may be based on artificial neutral network techniques or algorithms which are very good in recognizing patterns and adapting to them. Other pattern recognition schemes will also be examined to further explore the design space of wear-reducing architectural-level policies. Wear-aware hardware augmentations to the base CMP architecture will be implemented using hardware description languages (e.g., VHDL) to prove their feasibility.

Required Qualifications: Candidates should possess a Master’s-level degree in the field of Computer Science, or Computer Engineering, or Electrical Engineering. This research position falls under the themes of computer architecture, distributed computer systems, interconnection/computer networks, artificial neural network architectures, algorithms, computer programming in C/C++, hardware-description languages (such as VHDL or Verilog) and circuit synthesis, and to some extent mathematics.

Research Advisor:  Vassos Soteriou, Associate Professor, vassos.soteriou@cut.ac.cy

 

  • One (1) post in the following field: “Design of Hardware-Level-Secure and Trustful Multi-Core Processors and their Networks-on-Chips (No’s)”

Description: Today our modern societies rely more and more on information technology (IT), in which trustworthiness, reliability and secure information handling have become key expectations and requirements. Despite this, various malicious parties have repeatedly attempted to steal and manipulate user data so as to cause damage, source quick and unlawful financial gain, and steal sensitive information such as user identities and military/corporate secrets, etc. Until recently, these parties have focused on the software components of computers to gain access to such sensitive information, however recently; unfortunately the computer hardware itself has been misused and tampered so as to gain access to such info. These parties make use of various hardware vulnerabilities that either resides in the existing integrated circuit production chain, or directly within the processor hardware and its design.

This research topic will investigate and develop various techniques to empower the “design of processor and interconnect circuits for trust” so as to effectively protect and secure personal data within the computing hardware itself. It will focus on leveraging recent advances seen in multi-core processors and their contained on-chip interconnects so as to lock, or render the underlying digital electronics unusable, should a malicious entity attempt to steal, compromise, misuse or tamper with a physical processor. As such, dedicated physical features will be researched, developed and incorporated into existing off-the-shelf processor designs (such as the ARM M0+ microcontroller as a base) to showcase robust and resilient protection of personal data at the hardware level.

Required Qualifications: Candidates should possess a Bachelor’s Degree, preferably a Master’s-level postgraduate degree, in either the field of Computer Science, or Computer Engineering, or Electrical Engineering. This research position falls under the themes of computer architecture, distributed systems, interconnection/computer networks, security algorithms, computer programming in C/C++, the usage of hardware-description languages (such as VHDL or Verilog), and to some extent mathematics.

Research Advisor:  Vassos Soteriou, Associate Professor, vassos.soteriou@cut.ac.cy

 

  • One (1) position in the following field: “Mathematical modeling and performance analysis of micro-network router architectures and traffic flows”

Description: This research topic concentrates on elaborate detailed mathematical models to capture in detail the behavior of the architecture of pipelined micro-routers utilized in micro-interconnect networks found in today’s multi-core processors and embedded systems. Various state-of-the-art architectures will be considered. The interaction of the underlying router organization will be considered in tandem with various flow-control protocols and routing algorithms, along with numerous traffic flow spatio-temporal behaviors in order to determine throughput and network latency levels that will act as indicators of architectural router performance. Results obtained from software simulations of equivalent architectures will be carried out to confirm the validity and the accuracy of the mathematically-modeled micro-router architectures.

Required Qualifications: Candidates should possess a Bachelor’s Degree and a Master’s-level postgraduate degree from accredited universities in the field of Computer Science, or Electrical Engineering, or Computer Engineering or Mathematics with a preferred specialization in computer architecture, computer networks, discrete mathematics, statistics, or related.  The candidate should have 2+ years of experience in object-oriented programming and be fluent in C++ programming and/or Python. A strong mathematical background is desired. Excellent command of the English language is a must.

Research Advisors:  

Vassos Soteriou, Associate Professor, vassos.soteriou@cut.ac.cy

Paul Christodoulides, Assistant Professor, paul.christodoulides@cut.ac.cy

 

  • Four (4) Posts  in any of the following subjects:

“Automated Software Testing”

Description: Methods, techniques, models and algorithms for performing software testing in an automated way, with little or no human intervention. Use of Computational Intelligence or/and of other sub-areas of Computer Science for performing black-box (specifications-based) and glass-box (source code-based) testing for classic software systems, web applications and mobile software.

Required qualifications: BSc and/or MSc in Computer Science or Computer Engineering or Informatics or any other related field. Prior experience or specialization (i.e. during BSc or MSc in Software Engineering) will be considered as advantage.

«Smart Manufacturing – Industry 4.0»

Description: Smart Manufacturing is a term coined by several agencies like the Department of Energy (DoE) and the National Institute of Standards and Technology (NIST) in the United States. Smart Manufacturing is described in short as “a data intensive application of information technology at the shop floor level and above to enable intelligent, efficient and responsive operations”. There are multiple more comprehensive definitions available and they all highlight the use of Information and Communication Technology (ICT) and advanced data analytics to improve manufacturing operations at all levels of the supply network, be it the shop floor, factory, or Supply Chain. The fourth industrial revolution is characterized by the introduction of the Internet of things (IoT) and Internet of services concepts into manufacturing, which enables smart factories with vertically and horizontally integrated production systems. In industries worldwide, highly flexible processes that can be changed quickly enable individualized mass production. Variants are self-determined through items delivering their own production data to intelligent machines, which are aware of the environment, exchange information, and control processes in production and logistics by themselves. Data are collected along the entire life cycle in large quantities and stored decentralized to enable local decisions; however, the said data are still transparent to be exchanged with partners. In order to realize this vision, elements such as machines, storage systems, and utilities must be able to share information, as well as act and control each other autonomously. Such systems are called cyber-physical systems (CPS). The research to be conducted will revolve around the aforementioned concepts and will utilize forms of smart data processing, visualization & analytics, IoT, CPS and production line automations through sensing and actuating. This topic will be investigated with the support of local industrial collaborators (Muskita, Paradeisiotis) that will offer a real-world environment (and data) for experimentation and validation.

Required qualifications: BSc and/or MSc in Computer Science or Computer Engineering or Informatics or any other related field. Prior experience or specialization (i.e. during BSc or MSc in Software Engineering) or any involvement with research in the past will be considered as advantage.

«Automatic Resource Management for the Cloud»

Description: This research topic will concentrate on algorithms, methods and techniques for automating certain process in the Cloud environment dealing with how resources are managed. More specifically, Computational Intelligence – CI approaches will be utilized to tackle issues and solve problems related to optimizing the way resources are managed (e.g. physical servers, virtual machines, etc.) in such a way so that clients are serviced according to their Service Level Agreements – SLA, with high quality and performance, but at the same time energy and cost preservation is taken into consideration. Fog computing will also be investigated as the paradigm that pushes processing intelligence and data down to the local area network level of network architecture and a fog node to avoid latencies.

In this context different CI models will be investigated and apply in single- and multi-objective optimization of Cloud resources.

Required qualifications: BSc and/or MSc in Computer Science or Computer Engineering or Informatics or any other related field. Prior experience or specialization (i.e. during BSc or MSc in Software Engineering) or any involvement with research in the past will be considered as advantage.

"Software Engineering and Intelligent Data Processing in Distributed Block chain Processing Systems"

Research will focus on methodologies and techniques for the development of software systems for distributed processing in the new computational model of Blockchain. Particular emphasis will be placed on the automation of smart data processes in this environment, using models and algorithms of Computational and Artificial Intelligence, as well as single and multi-objective optimization methods. This subject will apply research results to real-world systems that are already running or are going to be developed in the Block chain environment, mainly from the Financial Sector, and may be supported by local private organizations by means of data provision and/or funding (currently in discussions with positive reactions).

Required qualifications: BSc and/or MSc in Computer Science or Computer Engineering or Informatics or any other related field. Prior experience or specialization (i.e. during BSc or MSc) in Software Engineering and/or Computational or Artificial Intelligence, or any involvement with research in the past will be considered as advantage.

Research Advisor: Andreas S. Andreou, Professor, andreas.andreou@cut.ac.cy

 

  • One (1) post in the following field: “Event Detection, Localization and Tracking using Wireless Sensor Networks”

Description: Wireless Sensor Networks (WSNs) are a fairly new technology that can potentially provide an interface between the physical world and computers allowing the latter to vanish into the background. They have a wide variety of applications including military sensing, infrastructure security, environment and habitat monitoring, industrial sensing, building and structure monitoring, and traffic control.  The proposed research is expected to be based on ideas and techniques from a variety of different fields including Wireless Communication Systems, Computer Networks, Collaborative Signal and Information Processing and Computational Intelligence. The offered positions will concentrate on the development of new algorithms and techniques for detecting, localizing and tracking an event. The developed algorithms should feature low computational complexity, distributed implementation and fault tolerance in order to address the limitations of WSNs in terms of energy and bandwidth and the harsh conditions of operation. The successful applicants are expected to perform real–time experiments in order to verify the performance of their algorithms using the WSN platform at the Cyprus University of Technology.    

Required qualifications: BSc (required) and MSc (preferably) in Electrical Engineering and/or Computer Science. Prior research experience or specialization in related topics will be considered an advantage.

Research Advisor: Michalis Michaelides, Assistant Professor,   michalis.michaelides@cut.ac.cy

 

  • One (1) position in the following field: “Contaminant Event Monitoring in Intelligent Buildings”

Description: An Intelligent Building is a system that incorporates computer technology to autonomously govern and adapt the building environment in order to enhance operational and energy efficiency, cost effectiveness, improve user’s comfort, productivity and safety, and increase system robustness and reliability. The dispersion of contaminants from sources (events) inside a building can compromise the indoor air quality and influence the occupants' comfort, health, productivity and safety. These events could be the result of an accident, faulty equipment or a planned attack. Under these safety-critical conditions, immediate event detection should be guaranteed and the proper actions should be taken to ensure the safety of the people. The proposed research will investigate and produce solutions for the problem of monitoring the indoor building environment against the presence of contaminant events.  Distributed sensor networks have been widely used in buildings to monitor indoor environmental conditions such as air temperature, humidity and contaminant concentrations (e.g. CO, CO2). The goal of this research will be the development of methods for interpreting the real-time-collected data coming from the sensors in order to ensure the accurate and prompt identification of contaminant sources. The results can help determine appropriate control solutions such as: (i) indicating safe rescue pathways and/or refugee spaces, (ii) isolating contaminated spaces and (iii) cleaning contaminant spaces by removing sources, ventilating and filtering air.  

Required qualifications: BSc (required) and MSc (preferably) in Electrical Engineering and/or Computer Science. Prior research experience or specialization in related topics will be considered an advantage.

Research Advisor: Michalis Michaelides, Assistant Professor,   michalis.michaelides@cut.ac.cy

 

  • One (1) position in the following field: Air Quality Monitoring in Smart Cities using Wireless Sensor Networks

Description: Currently, there is a lack of sufficient infrastructure for environmental monitoring, both spatially (in multiple points) and temporally (in regular time intervals). The proposed wireless sensor network can constitute an economical and reliable solution to the problem of sufficient monitoring and control of the city air quality. The proposed research will focus on the development of innovative algorithms and techniques for detecting, identifying and tracking the release of pollutants in an urban environment using a wireless sensor network. More specifically, the successful candidate is expected to use signal processing and machine learning methods to analyze the collected data from the sensors in order to: (i) construct a fine-grained pollution map of the city, (ii) identify the main sources of pollution and estimate their locations, (iii) develop models for predicting the pollution levels in the near future. These results are expected to provide the necessary information for reducing the pollution levels through appropriate actions and policies, leading to a cleaner and safer city environment.  The successful applicants are expected to work with real data in order to verify the performance of their algorithms using the established WSN platform at the Cyprus University of Technology.

Required qualifications: BSc (required) and MSc (preferably) in Electrical Engineering and/or Computer Science. Prior research experience or specialization in related topics will be considered an advantage.

Research Advisors: Michalis Michaelides, Assistant Professor,   michalis.michaelides@cut.ac.cy

 

  • One (1) post in the following field: “Information and Communication Systems for Smart Ports”

Description: Ports have played a crucial role in connecting the Europe markets with island areas, such as Cyprus, as 74% of goods imported or exported from Europe travel through sea transport. The application of new information and communication systems and technologies can significantly improve the efficiency of the various port operations and services via enabling real-time situation awareness to all participants involved in maritime activities in the ports of Cyprus. The proposed research will investigate the implementation of such systems at the Port of Limassol for collecting real-time information related to ship movements, the environment, and the tracking of cargo by exploiting innovative technological solutions such as buoys, UAVs, and RFIDs. The collected information, will be further processed using advanced data analytics for ensuring high quality data, calculating KPIs, and creating new decision-support tools and services for maritime stakeholders. The successful applicants are expected to perform real–time experiments in order to verify the performance of the developed algorithms and solutions using the implemented systems at the Port of Limassol.     

Required qualifications: BSc (required) and MSc (preferably) in Electrical Engineering, or Computer Science, or related field. Prior research experience or specialization in related topics will be considered an advantage.

Funding: Funding is available for full-time qualified applicants through involvement in a nationally-funded Research Program.

Research Advisors:

Michalis Michaelides, Assistant Professor,   michalis.michaelides@cut.ac.cy

Herodotos Herodotou Assistant Professor, herodotos.herodotou@cut.ac.cy

 

  • One (1) post in the following topic: “Development of Optical Fiber Plasmonic Sensors and Nanoantennas Using Femtosecond Laser Pulses”

Required Qualifications:  BSc and/or MSc in Electrical Engineering or Physics, or any other related subject. Strong mathematical background will be considered an advantage.

The PhD will focus on the development of photonic (bio)chemical sensing platforms, using custom sensors developed in-house with a femtosecond laser system. The PhD will focus on tilted fibre Bragg gratings surrounded by nanoscale coatings of metal layers and nanoparticles that will be studied and optimized to exploit the plasmonic enhancement of the sensing transduction mechanisms.

Research Advisors:   Kyriacos Kalli, Professor, kyriacos.kalli@cut.ac.cy

 

  • One (1) post in the following topic:  “Optical Fibre Sensors for Biomedical Applications”

Required Qualifications: BSc and/or MSc in Electrical Engineering or Physics, or any other related subject. Strong mathematical background will be considered an advantage.

Research Advisors:   Kyriacos Kalli, Professor, kyriacos.kalli@cut.ac.cy

 

  • One (1) post in the following topic: IdeNtity verifiCatiOn with privacy-preservinG credeNtIals for anonymous access To Online services

The main purpose of INCOGNITO project is to develop a user-friendly authentication system that offers secure digital identity, privacy, and anonymity through the use of anonymous credentials. The program aims at designing and implementing an infrastructure that supports the anonymity of the user by using cryptographic anonymous credentials as well as Federated Login solutions. Also, this system, which can be a central entity, or distributed using blockchain, enables the user to consolidate, manage, and verify their identity safely by using physical identity documents and online accounts on the Internet.

The INCOGNITO consortium includes the Telecommunication operator Telefonica, the certSIGN computer security provider, the University of Piraeus, and small and medium-sized technology companies from Spain and Greece. The ultimate goalof the program is to evaluate the aforementioned technologies by end-users. More information on the work already done in this area by CUT can be found at the web site of the ReCRED (https://www.recred.eu/) research project, which has recently ended. CUT was the technical manager of ReCRED.

CUT’s main research fields in the CONCORDIA project are divided in three main pillars:

Privacy: The protection of user personal data on the web and the detection of personal data leakages to unauthorized parties, mainly the ad-ecosystem. The research around this field aims to result to tools able to detect such user data leakages. In addition, methods should be proposed to tackle such problems, based on advanced machine learning and deep learning techniques.

Identity management: This part focuses on the management, authentication and verification of users’ identity on Online Social Networks (OSN). The researcher assigned to tackle this problem will research and acquire blockchain knowledge since a blockchain-based identity verification and management ecosystem is aimed to be built in order to allow users to consolidate, authenticate and verify their real-world identities without the need to trust a centralized authority for storing and managing their personal information.

Cybersafety / Fake News: This part studies the detection of accounts (trolls/fake accounts) that disseminate disinformation on OSN. At the same time, it focuses on the analysis and detection of this information using advanced, innovative machine learning detection techniques.

In the CONCORDIA project participate big names in the areas of telecommunication namely, Telefonica and TELECOM Italia. In addition many well-known companies and organizations are part of the consortium, like AIRBUS, BMW, Siemens, and Caixa Bank. Also, distinctly recognized universities of Germany, Italia, Slovenia, Greece, England, Check Republic, Israel, Norway, Slovenia, Belgium, Holland, Luxemburg and France participate in this project.

More information on the work already done in this area by CUT can be found at the web site of ENCASE (https://encase.socialcomputing.eu/) research project. CUT is the Coordinator of ENCASE.

The Cyprus University of Technology participates in the above program with the NetSySci Lab (https://netsysci.cut.ac.cy/) under the umbrella of the Social Informatics Research Center (https://www.socialcomputing.eu/).

The PhD student will acquire, through studies and research, expertise in Networked Systems, Security, Cybersafety and Large Scale Data Processing. He/she will be called to research and develop methods for large scale extraction of Online Social Network (OSN) information and perform analysis on that data.

The successful applicants should be able to demonstrate excellent knowledge of CS theory as well as outstanding software implementation skills.

Required Qualifications:              

  • BSc or MSc from a recognized university in Electrical Engineering or Computer Science.
  • Programming experience in a high-level programming language
  • Very good knowledge of English (spoken and written).
  • Organizational skills.
  • Participation in funded research programs will be considered as an additional qualification
  • Prior research experience or specialization in Computer Security will be considered an advantage.

Funding prospects: The selected candidate will be funded by the European Commission’s Horizon 2020 framework program.

Research Advisor: Michael Sirivianos, Associate Professor, michael.sirivianos@cut.ac.cy.

 

  • One (1) post in the following topic: Α Security ECONomics service platform for smart security investments and cyber insurance pricing in the beyonD 2020 netwOrking era”

The main purpose of the SECONDO project is to optimize decisions on cyber-security investments and insurance pricing. Simply put, the program aims to support professionals seeking investment in cyber security. It is a top-of-the-line research problem, as the rapid development of cyber-attacks is expected to continue its upward course.

SECONDO therefore proposes a unique, scalable, highly interoperable platform that encompasses a comprehensive cost-driven methodology for: (i) estimating cyber risks based on a quantitative approach that focuses on both technical and non-technical aspects, (e.g. users behaviour), that influence cyber exposure; (ii) providing analysis for effective and efficient risk management by recommending optimal investments in cyber security controls; and (iii) determining the residual risks and estimating the cyber insurance premiums taking into account the insurer’s business strategy, while eliminating the information asymmetry between the insured and insurer.

The aim of the SECONDO PhD researcher position is to combine statistical and technical knowledge to develop innovative cyber-security software and algorithms that will help users make decisions about investment, risk assessment, and pricing of insurance.

The SECONDO project involves the University of Piraeus and Surrey, as well as small and medium-sized technology and research companies from Cyprus, Greece and Spain.

The Cyprus University of Technology participates in the above program with the NetSySci Lab (https://netsysci.cut.ac.cy/) under the umbrella of the Social Informatics Research Center (https://www.socialcomputing.eu/).

The successful applicants should be able to demonstrate excellent knowledge of CS theory as well as outstanding software implementation skills.

Required Qualifications:              

  • BSc or MSc from a recognized university in Electrical Engineering or Computer Science.
  • Programming experience in a high-level programming language
  • Very good knowledge of English (spoken and written).
  • Organizational skills.
  • Participation in funded research programs will be considered as an additional qualification
  • Prior research experience or specialization in Computer Security will be considered an advantage.

Funding prospects: The selected candidate will be funded by the European Commission’s Horizon 2020 framework program.

Research Advisor: Michael Sirivianos, Associate Professor, michael.sirivianos@cut.ac.cy.

 

  • One (1) post in the following topic:  “Night Cooling Systems: Modeling and monitoring systems”
  • Or one (1) post in the following topic:  “Theoretical and Experimental investigation of geothermal systems”

Required Qualifications:  BSc and/or MSc in Electrical Engineering and Computer Engineering or Computer Science or Physics, or any other related subject. Strong mathematical modeling background will be considered an advantage.

Research Advisor:  Paul Christodoulides, Assistant Professor, paul.christodoulides@cut.ac.cy

 

Information:

Department Secretary

Tel: 25002533, Fax: 25002635