Master's Thesis Openings in Theoretical and Computational Chemistry, Machine Learning, and Biophysics

The group at École normale supérieure (PSL Research University) in Paris, France, led by Guillaume Stirnemann, is offering several Master's thesis opportunities for 5-6 months starting in January or February 2026. The research topics include machine-learned interatomic potentials for chemical reactivity with applications to electrocatalytic reduction of carbon dioxide (in collaboration with Damien Laage), prebiotic chemistry (with A. Marco Saitta), generative AI and chemical reactivity (with Marylou Gabrié and Damien Laage), and the effect of hydrostatic pressure on lipid and protein dynamics in GPCR systems (with Jérôme Hénin). These projects are highly interdisciplinary, combining theoretical chemistry, computational chemistry, machine learning, artificial intelligence, biophysics, and molecular dynamics. Candidates must be enrolled in a Master's program or equivalent and have a strong academic record in physics, chemistry, computer science, or related fields. Some positions have secured funding, while others will seek funding, and all may be extended into PhD opportunities upon mutual agreement. Interested students are encouraged to contact the group for further details and to apply. The environment is collaborative, with opportunities to work alongside leading researchers in the field.