Studies start in January 2024

Deadline for applications: Friday, 24th of November 2023 (11:59 p.m.)

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Information from the Department Secretary:

Contact Form |Tel. 25002533 | Fax: 25002633

• One (1) position in the following field: The Transformation of the Arts from the Early Era to the Age of Postmodern Digital Representation and Algorithmic Art Based on Machine Learning and Artificial Intelligence

Description: Artificial Intelligence and Machine Learning have significant potential for customization for creative purposes. This study examines approaches to these areas in terms of artistic practice and creative processes from the earliest times (Harold Cohen AARON 1970) to the present. In a following stage the study explores the historical relationship between visual art, new media and technology in the postmodern stage of development of artificial intelligence. (j) Interactive program (e-author, Richard Grusin), (ii) Database evaluation system to facilitate visual development of young artists with critical principles, (iii) Program creation and data collection based on my personal visual research as a development record, image production and as an electronic creative and research guide, (iii) Selection system based on neuroaesthetics in art.

Required Qualifications: Necessary degree or postgraduate level 7 of the National and European Qualifications Framework, Department of Visual or Applied Arts, as well as familiarity with generative artificial intelligence (generative AI) through the HuggingFace platform.

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

• One (1) position in the following field: Applications of conversational AI for the promotion of the average physical condition of the population

Description: Conversational AI can help in promoting physical exercise for people with sedentary life. Conversational AI, also known as chatbot technology, may be used to create engaging and personalized experiences that can help people to stay motivated and reach their fitness goals.

This thesis will aim to practically explore some specific ways that conversational AI can be used to promote physical exercise. These may include:

• Provide motivation and support.
• Create personalized exercise plans.
• Track progress and provide feedback.
• Educate and inform.

The thrust of the thesis will concentrate on supervised fine-tuning of foundational models as well as their user alignment via reinforcement learning trough human feedback. The outcome will be novel large language models addressing the aforementioned objectives.

The successful applicant will necessarily have interdisciplinary skills that combine both sport sciences and computer programming, with interest in PyTorch programming and affinity with HuggingFace models.

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

• One (1) position in the following field:  Development of Operational Models via Artificial Intelligence in the Agri-Food Sector to Enhance the Environmental Footprint of Producers and Enterprises

Description: The agricultural and food production sector plays a critical role in ensuring food security and sustainability, but it also significantly contributes to environmental challenges, such as resource depletion, greenhouse gas emissions, and soil degradation. To address these pressing issues, this PhD thesis focuses on the development of operational models through Artificial Intelligence (AI) techniques within the agri-food sector. The aim is to enhance the environmental footprint of both agricultural producers and businesses operating within this sector. We will utilize AI and machine learning algorithms to develop decision support systems that enable farmers and agri-food businesses to make informed and sustainable choices in their operations.

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

• One (1) post in the following topic:  Using Graph Neural Networks to Analyze Team Interactions and Improve Football Coaching Strategies

Description: Graph Neural Networks (GNNs) represent one of the most captivating and rapidly evolving architectures within the deep learning landscape. As deep learning models designed to process data structured as graphs, GNNs bring remarkable versatility and powerful learning capabilities.

Football coaches always look for ways to improve their team's performance, as a group or separately as individual players, and gain a competitive advantage over their opponents. The current methods of team performance analysis include video analysis made by humans, which is time-consuming and subject to human bias. Nevertheless, recent advances in machine learning, especially Graph Neural Networks (GNNs), furnish a new way to study team interactions and enhance coaching strategies.

The suggested Ph.D. project will investigate the use of GNNs to analyze team interactions in football and develop new coaching strategies based on the insights gained. The research will collect and analyze data from professional football matches, including video footage and tracking data, to build a graph representation of team interactions to find the most effective approach for analyzing team interactions, including semi-supervised and unsupervised learning methods.

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.

Research Advisors: Michael Sivirianos , Assistant Professor, michael.sirivianos@cut.ac.cy.

• One (1) post in the following field: Predictability of Complex Networks

Description: Complex networks are everywhere - from the internet and social media to transportation systems and the human brain. These intricate systems are composed of nodes and edges, representing entities and their interactions. Understanding their structure and dynamics is crucial for addressing pressing challenges in fields as diverse as epidemiology, finance, and social sciences. For instance, by analyzing contact networks one can predict disease outbreaks and optimize vaccination strategies, contributing to public health. Further, by leveraging networks, one can design efficient urban transportation systems to promote sustainability and address urbanization challenges. Additionally, by studying protein-protein interaction networks one can shed light on the foundation of diseases and offer potential drug targets, advancing healthcare research and treatments. Finally, by studying social network dynamics one can explore the spread of information, influence, and behaviors in online and offline social networks.

As a PhD candidate, you will develop cutting-edge network models and algorithms, with an emphasis on the predictability of real-world networks, analyze large-scale real-world network data, and contribute to solving critical societal challenges. For further information please contact the Research advisor.

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

• One (1) post in the following field: 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, and mobile software applications.

Required qualifications: BSc and 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 an advantage.\

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

• One (1) post in the following field:  Smart Data Processing in Healthcare

Description: Exploitation of approaches such as Business Process Mining, Digital Twins and Blockchain for healthcare. In this context it is anticipated that the research work to be conducted will revolve around optimization of healthcare processes in terms of time to service, cost, and utilization of resources. Digital twins will be investigated as interactive means for performing simulations and for depicting graphically the analysis of the data involved and the outcome of decisions taken. Finally, Blockchain, and especially Ethereum Virtual Machines and smart contracts will be employed to provide an additional layer of security for healthcare transactions and data exchange.

Required qualifications: BSc and 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 an advantage.

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

• One (1) post in the following topic: “System for extraction and monitoring markers for developmental disorders evaluation in teenagers and children”

Description: Developmental disorders like developmental language disorder can affect teenagers or children speaking, listening and writing abilities. Definition of markers which can be used to identify such disorders, will be the main purpose of this PhD work. Several techniques for speech and language analysis as well as techniques for facial expression recognition will be applied in order to define these biomarkers.

Required Qualifications:Candidates are expected to have a strong background in a related field, such as computer science, biomedical engineering, as well as experience in digital signal processing, imaging and programming in Python language.

Degree in Computer Science or Biomedical Engineering or relevant fields.

Research Advisors: Efthyvoulos Kyriacou, Assistant Professor, efthyvoulos.kyriacou@cut.ac.cy    

• Two (2) positions in the following field: “Quantum Key Distribution (QKD)”

Description: Quantum key distribution (QKD) is the only technology that can provide unconditional security in communications. For this reason, the EU has requested, through the European Quantum Communication Infrastructure (EuroQCI) initiative, from all EU member states to implement local quantum networks. In Cyprus this will be implemented through the Cyprus Quantum Communication Infrastructure (CYQCI), to which the specific positions belong. For more information on the project, you can follow the website: https://cyqci.eu/index.html.

The aim of the research will focus on the following:

• The development of a prototype optical fiber based QKD system 
• The implementation of national QKD links  
• The development of simulation codes for QKD systems 

Therefore, the research will include extensive work with optical fibers, lasers and electronics. 

Applicants should have: 

• Bachelor's or master's Degree from a recognized University in the relevant subjects (Physics/ Electronic or               Computing Engineering) 
• Experience with research projects from national and/or European funds will be considered an advantage 
• Organizational skills 
• Excellent knowledge of the English Language 
• Knowledge of Python or other programming languages would be a plus. 
• Experience in conducting research related to the subject will be considered an advantage 

The research activity will include:

• Development and deployment of new software defined network control for quantum networks.
• Analysis, implementation, and contribution to published standards related to quantum key distribution network orchestration and control interfaces.
• Development of application-level software to implement cryptographic functions based on quantum cryptography.
• Writing detailed documentation to describe the developed software.
• Working closely with the rest of the team and demonstrating effective communication with other colleagues.
• Perform other job-related duties as assigned.

Funding: The successful candidate will be employed as a Postgraduate Associate in the Photonics and Optical Sensors research laboratory (PhOSLab)

Offer competitive financial support with exact salary level to be determined at interview.

Tuition will be covered according to performance per semester

Duration: 36 months

Start: January 1, 2024

The CYQCI project is co-funded by the European Commission and the Cyprus Deputy Ministry of Research, Innovation and Digital Policy under the Grant Agreement No. 101091655.

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