RECRUITMENT LIMITS FOR THE DOCTORAL SCHOOL IN THE ACADEMIC YEAR 2026/2027

Institute of Theoretical and Applied Informatics, Polish Academy of Sciences – 0 PLACES
Institute of Computer Science, Polish Academy of Sciences – 2 PLACES
Institute of Fundamental Technological Research, Polish Academy of Sciences – 0 PLACES
National Information Processing Institute, National Research Institute – 0 PLACES
Research and Academic Computer Network - National Research Institute – 0 PLACES
Institute of Biocybernetics and Biomedical Engineering, Polish Academy of Sciences – 0 PLACE
Systems Research Institute, Polish Academy of Sciences – 0 PLACES

The above admission limits apply to recruitment conducted in June/July 2026.

Proposed topics of doctoral dissertations 2026/2027

Recruitment for doctoral studies in cooperation with IDEAS NCBR

Research work offer for PhD students proposed by IDEAS NCBR

BIOMEDICAL ENGINEERING AND MEDICAL SCIENCES

No	Topic	Supervisor	Institute
	Piezoelectric biodegradable scaffolds for chronic wound healing	Paweł Sajkiewicz	IPPT PAN
	Stimuli-responsive polymer hydrogels for the regeneration of post-infarction myocardium	Paweł Sajkiewicz	IPPT PAN
	Polymeric scaffolds for anticancer therapies	Dorota Kołbuk-Konieczny	IPPT-PAN

INFORMATION AND COMMUNICATION TECHNOLOGY

No	Topic	Supervisor	Institute
	Applied cryptography and privacy protection	Mirosław Kutyłowski Przemyslaw Kubiak	NASK PIB
	AI-Driven Solutions for Early Pancreatic Cancer Diagnosis and Therapy	Agnieszka Pręgowska	IPPT PAN
	Computationally efficient algorithm for large-scale structural topology optimization subject to stress constraints	Bartłomiej Błachowski	IPPT PAN
	Computer vision-based civil infrastructure monitoring using physics-based graphics models	Bartłomiej Błachowski	IPPT PAN
	Transmission efficiency and reliability in neural networks inspired by brain architectures. Information Theory and Machine Learning Approach	Agnieszka Pręgowska, Janusz Szczepański	IPPT PAN
	Performance evaluation of tradeoffs between resiliency, reliability and energy efficiency in low power long range wireless networks	Krzysztof Grochla	IITiS PAN
	Interpretability of Deep Reinforcements Learning Agents	Przemysław Sekuła	IITiS PAN
	Model Checking Parametric Timed Strategic Abilities	Wojciech Jamroga Wojciech Penczek Laure Petrucci	IPI PAN LIPN, CNRS Universite Sorbonne
	Implicit neural representations for biomedical image analysis	Michał Byra	IPPT PAN
	KAN-based anomaly detection in IoT and engineering systems	Joanna Kołodziej	NASK PIB
	Deep Reinforcement Learning and Game-Theoretic Frameworks for Solving Complex Multi-Agent Environments	Agnieszka Pręgowska	IPPT PAN