Research Associate Position(s): “Learning Agents and Robots” Multidisciplinary Research Group (MRG) - Θέσεις εργασίας Κύπρος

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Research Associate Position(s): “Learning Agents and Robots” Multidisciplinary Research Group (MRG)

Research Associate Position(s): “Learning Agents and Robots” Multidisciplinary Research Group (MRG)

The Research Centre on Interactive Media, Smart System and Emerging Technologies – RISE ( is a newly founded research centre of excellence in Nicosia, Cyprus. RISE is a significant investment supported by the European Commission, the Republic of Cyprus and its founding Partners, the Municipality of Nicosia, Max Planck Institute, University College London, the University of Cyprus, the Cyprus University of Technology and the Open University of Cyprus.
The Centre conducts excellent, internationally competitive scientific research in the areas of visual sciences, human factors and design, communication, and artificial intelligence delivered by high-calibre multidisciplinary research teams. RISE engages in knowledge transfer and innovation activities aiming to bridge the gap between scientific research and STEM-led innovation and entrepreneurship.
The Learning Agents and Robots (LEAR) MRG focuses on creating software agents and robots that learn to understand the world, solve tasks, interact with humans and make adaptive decisions in complex, dynamic and uncertain environments. The research interests of the group span the fields of machine learning (in particular, reinforcement learning and deep learning), planning under uncertainty, optimal control, multiagent systems, evolutionary computation and robotics. We are looking for research associates with experience in “robot learning”, “reinforcement learning” and/or “deep learning” (see more details about qualifications below).
The successful candidate will have the opportunity to conduct fundamental and/or applied research in the aforementioned areas. The position holder will also participate in the preparation of research proposals for funding, project reports and deliverables, and travel abroad for dissemination activities. Furthermore, position holders should publish/present their research results in prestigious international conferences and journals and contribute to the research centre’s key performance indicators. The successful candidate will work under the supervision of the LEAR MRG Team Leader, Dr Vassilis Vassiliades.

Bachelor’s and/or postgraduate degree in a relevant field (Robot Learning / Reinforcement Learning / Deep Learning / Planning / Optimal Control / Machine Learning / Artificial Intelligence) from an accredited institution.
Team player with self-motivation and the ability to work independently, rapidly prototype, learn quickly and explain complicated concepts in simple terms.
Strong coding skills in Python and/or C++.
High-impact research publications on relevant topics (a must for PhD holders/an advantage for non-PhD holders).
Experience with machine learning and deep learning (e.g., libraries such as TensorFlow, PyTorch, etc., or processing various types of data such as images, videos, sequences, signals, text, graphs, point clouds etc.) is highly desired.
Experience with planning, optimal control, (contextual) bandits, or reinforcement learning (e.g., in MDPs, POMDPs, games) is highly desired.
Experience with robot learning (including working with ROS, robotic simulators (such as Gazebo, V-REP), physics engines (such as Bullet, ODE, MuJoCo) and/or physical robots) is highly desired.
Strong mathematical background (e.g., linear algebra, multivariate calculus & optimization, probability theory & statistics, algorithms & complexity, information theory, control theory) will be considered an advantage.
Previous grant-writing experience will be considered an advantage.
Previous relevant industrial experience will be considered an advantage.
Excellent knowledge of both spoken and written English language.
For non-EU applicants a work permit will be required.

A very attractive remuneration package will be offered to successful candidate according to qualifications and experience. Membership to RISE Employee Medical Scheme and RISE Provident Fund.

Application Process

Interested candidates should submit the following items via email to
and use the Email subject line: "Application: Research Associate(s) LEAR"
A cover letter which clearly specifies (i) employment availability date, (ii) part-time and/or full-time availability and (iii) rationale on why you think you would be a good fit for the position within the LEAR MRG
Description of their academic and research experiences as well as any relevant industrial experience where applicable (500 words maximum)
A detailed CV
Copies of degree certificates (BSc/MSc/PhD)
Two representative publications (if applicable)
Contact details of two referees, either two University professors or one University professor and one industry referee.
Note that if you previously applied for a post at RISE, a new application is required.
Deadline: Position open until filled.

For general inquiries, applicants may contact the HR Department of the Research Centre on Interactive Media, Smart Systems and Emerging Technologies at

The applicants may address any technical or research related inquiries to the LEAR MRG team leader Dr Vassilis Vassiliades at
All applications are treated in the strictest confidence.