Shortly

• I work at the Institute of Theoretical Physics, Wroclaw University.

• I am interested in particle, nuclear and computational physics. I am also an enthusiast of new computationals technologies such as Deep Learning.

• I am an author of publications in the following arxiv categories: hep-ph, hep-th, hep-exp, nucl-th, nucl-ex, physics.comp-ph, cond-mat.dis-nn, physics.flu-dyn, cs.lg, stat.ML

Available Positions:

I am seeking strong postdoctoral candidates for a Marie Skłodowska-Curie Postdoctoral Fellowship (MSCA PF) application with the University of Wrocław. The 2026 call is open and the deadline is 9 September 2026. (for more information see: https://bpr.uwr.edu.pl/uniwersytet-wroclawski-msca-pf/)

Possible project themes:

• AI-driven models for electron and neutrino collisions with atomic nuclei
• AI-supported searches for new physics
• Understanding physics through deep learning models

Researchers with interests in AI/ML and fundamental physics are very welcome to get in touch. #MSCAPF #PostdoctoralFellowship #ArtificialIntelligence #ParticlePhysics #DeepLearning

Current Projects I am involved in

• Deep Learning for neutrino interactions with nuclei
• Bayesian Neural Networks for Partial Differential Equations
• Deep Learning for Physics of Fluids
• Algebraic Structures for SuperGravity

Available Ph.D. or MSc. topics

A) Deep learning in Physics The project concerns studies and applications of deep learning methods in physics. Three directions of research are distinguished:

• Deep learning for neutrino interactions;
• Physics-informed, guided and inspired Neural Networks
• Teaching physics neural networks