KIOS RESEARCH AND INNOVATION CENTER OF EXCELLENCE
Special Scientist for Research –
Research Associate (Digital Health)
Title : Special Scientist for Research (Research Associate) No. of Positions : One (1) Category : Employment contract Location : University of Cyprus, Nicosia, Cyprus The KIOS Research and Innovation Center of Excellence (www.kios.ucy.ac.cy) at the University of Cyprus announces one (1) Special Scientist for Research (Research Associate) position, focusing on Digital Health, for full-time employment. The successful candidate will contribute to interdisciplinary research projects focusing on the analysis of electroencephalography (EEG) and multimodal wearable sensor data for mental health, stress assessment, sleep monitoring, cognitive state analysis, and digital biomarkers. Who we are: The KIOS Research and Innovation Center of Excellence is the largest research center of its kind in Cyprus and one of Europe’s leading Centers of Excellence. It combines world-class academic research with realworld application through its innovation driven environment. Currently, the Center employs more than 200 people who are supported by externally funded research and innovation projects and has strong international collaborations, translating advanced research into impactful solutions. The KIOS CoE operates in a diverse environment as an equal opportunity employer. The Center is internationally recognized, receiving significant national and international awards and distinctions such as ERC Grants from the European Council, an IEEE Frank Rosenblatt Technical Field Award, Digital Water Award 2024 by Water Europe, multiple National New Researcher of the Year Awards, National Innovation & Entrepreneurship Awards, and several Best Paper Awards in top-tier international conferences and journals. What we do: KIOS provides an inspiring environment for carrying out top level research and innovation in the area of Information and Communication Technologies, with emphasis on the Monitoring, Control and Security of Critical Infrastructures. Such infrastructures include power and energy systems, water networks, transportation networks, telecommunication networks, healthcare systems, and emergency management and response systems. The Center instigates interdisciplinary interaction and promotes collaboration between industry, academia, and research organizations in high-tech areas of global importance. Why work at KIOS: You will contribute to high-profile projects, both locally and globally, with opportunities to publish in toptier journals and conferences, grow professionally, and take ownership in a dynamic, intellectually rigorous environment. You will collaborate closely with leading academics and multidisciplinary teams, advancing cutting-edge research and translating it into real-world deployments across critical infrastructure systems, while seeing your work delivering tangible impact on today’s most important challenges. We offer a flexible and supportive environment, along with opportunities for continuous training and professional development. Job Details The successful candidate is expected to:- Develop and implement advanced signal processing and AI methodologies for electroencephalography (EEG) and physiological data analysis.
- Analyze and interpret multimodal wearable data including electroencephalography (EEG), electrocardiography (ECG), photoplethysmography (PPG), accelerometry, sleep, and activity monitoring signals.
- Design and evaluate machine learning (ML) and deep learning models for stress detection, sleep analysis, mental wellbeing assessment, fatigue monitoring, and cognitive state prediction.
- Develop real-time or near real-time monitoring pipelines.
- Contribute to research publications, technical reports, and EU/national funded projects.
- Collaborate with interdisciplinary teams including clinicians, psychologists, engineers, and data scientists.
- Attention to detail
- Problem solving skills
- Team-player
- Reliable and trustworthy
- Flexible and eager to learn
- Able to adapt in a fast-paced dynamic environment
- Have good communication, organizational and self-management skills
- Excellent knowledge of the English language
- Electroencephalography (EEG) signal processing and neurophysiological data analysis
- Biomedical signal analysis: electroencephalography (EEG), electrocardiography (ECG), photoplethysmography (PPG), electromyography (EMG), wearable sensing
- AI/ML for health applications
- AI/ML for mental health, stress, sleep, or wellbeing applications
- Time-series analysis and digital biomarker development
- Deep learning frameworks (e.g., PyTorch, TensorFlow)
- Statistical analysis and data visualization
- Wearable technologies and physiological monitoring systems
- Programming in Python, MATLAB, or related languages
- Bachelor’s or/and Master’s Degree in Electrical Engineering or Computer Engineering or Biomedical Engineering or Computer Science or Data Science or Neuroscience or Psychology or Biomedical Informatics or Artificial Intelligence or a related field from an accredited institution.
- Doctorate degree or equivalent in Biomedical Signal Processing, EEG Analysis, AI in Healthcare, Neurotechnology, Wearable Sensing, Computational Neuroscience, Digital Mental Health or a related field from an accredited institution.
- Experience with wearable devices, physiological sensing, sleep analysis, stress monitoring, or mental health datasets will be considered an advantage.
- Publications in relevant scientific journals/conferences will be considered an advantage.
- Cover letter explaining the interest of the applicant in pursuing a career at the KIOS CoE, along with employment availability date, in English
- Short summary of prior work experiences, activities and accomplishments (can be combined with the cover letter), in English (2 pages maximum)
- A detailed curriculum vitae in English
- Copies of transcripts of BSc/MSc/PhD or other degree(s)
- Copy of an English language certificate (if any of your degrees were taught in English, this will be considered equivalent to an English language certificate)
- Contact details of at least two referees that can provide reference letters




