AIPHY - PhD Positions for Machine Learning in Particle Physics

Artificial intelligence not only pushes the boundaries of efficiency and precision in data analysis but transforms the way we think about data in scientific contexts. At the same time high energy physics is building on decades of experience in high quality data analysis combining rigorous uncertainty treatments with a fundamental understanding of data from quantum field theory.

The AIPHY program brings together experts from particle physics and computer science to develop new AI methods in the context of particle physics. The program builds an interdisciplinary PhD network between universities and research institutes in Copenhagen, Geneva, Heidelberg, Milan and Paris.

In this context we invite applications for 3 three-year PhD fellowships open to doctoral students recruited internationally. Candidates are expected to have a Master’s degree in Physics, Computer Science or closely related fields like mathematics. Excellent communication skills (including proficiency in English) as well as enthusiasm for interdisciplinary work are essential for all projects. The successful applicant will enrol in the graduate program of the respective university starting the academic year 2025-2026 (fall 2025) and will be expected to complete the requirements for a PhD by the end of the academic year 2027-2028.

He will also be expected to work co-operatively within the network, participate in European training events, and spend several months at the partner institutes as well as a secondment in a private-sector partner of the network.

The research topics focus on the development of new physics inspired AI methods for inverse problems, uncertainty estimation and explainable AI. Computer science based projects will focus on the method development while physics based projects will include an application theoretical or experimental physics. While the main supervisor will be either from computer science, experimental or theoretical physics, one co-supervisor will be from the complementary field.

Formal application for each of the three open positions will have to be sent through the HGSFP application portal (https://www.physik.uni-heidelberg.de/hgsfp/login.php) which will open on the 7th of February 2025.

The application requires a CV, research statement and at least two letters of recommendation.

However, interested candidates should contact their preferred institutes by mail before the application deadline.

Milan

Title: New Generative Models for Parton Distributions

Supervisor: Stefano Forte (Stefano.Forte@mi.infn.it), Stefano Carrazza (stefano.carrazza@mi.infn.it).

Institution: Department of Physics, University of Milan

Field: Theoretical Particle Physics

Paris

Title: Transfer Learning for jet energy scales

Supervisor: Anja Butter (anja.butter@lpnhe.in2p3.fr), Bertrand Laforge (laforge@lpnhe.in2p3.fr).

Institution: LPNHE, CNRS

Field: Theoretical/Experimental Particle Physics

Paris

Title: Extrapolation in ML

Supervisor: Gérard Biau (gerard.biau@sorbonne-universite.fr).

Institution: SCAI, Sorbonne University

Field: Computer Science