Course - AI-Accelerated Design And Optimisation of Compounds for Biological Applications

This one week workshop is part of a series of winter schools organized by PSL and its Qlife program in Quantitative Biology and taught at the Ecole Normale Supérieure (ENS) and Ecole Nationale Supérieure de Chimie de Paris (ENSCP)

Description

Recent technological developments in artificial intelligence (AI), machine learning
and computational approaches have enabled in-silico design of compounds for medicinal and biological purposes with unprecedented speed and precision.

The Qlife program in Quantitative Biology of the PSL University organizes a 5-day Winter School that will cover these cutting-edge approaches through a series of introductory lectures in the mornings, followed by digital workshops in the afternoons.
Evenings will feature keynote speaker seminars and poster presentations by the students.

The aim of this Winter School is to provide the attendees with a basic set of skills in different areas, including AI, TD-DFT, medical chemistry, photochemistry and chemical biology, with a clear emphasis on practical examples and guidance from experts in the field.

The workshop will provide

• Development of a machine learning workflow to predict photophysical properties
• Extend the machine learning concepts to more complex chemical systems
• Hands-on experience with a full machine learning workflow for molecular property prediction

Keywords

Digital practical, quantitative biology, TD-DFT, medical chemistry, photochemistry, chemical biology. 

_Application (deadline December 5th, 2025)_

The winter school is limited to 25 participants (attendance is competitive). It is open to M2 and PhD students, as well as postdocs, engineers and junior scientists with backgrounds in chemistry, life science, physics, computer science and mathematics. Knowledge or experience in the fields of design and optimisation of compounds is recommended.

Basic experience in file manipulation under Unix/Linux and coding ability in Python or R.

Registration fees: 150 € for academic participants (Fees covers lunches from Monday to Friday and some dinners).

Application procedure :

1) Register through the following link: https://forms.cloud.microsoft/e/cmYTdzpVgD
2) In addition, provide a CV, a motivation letter and a supporting letter from a supervisor as a single pdf file with “Qlife AI-accelerated Design WS2026_LASTNAME” as subject header to qlife.events@psl.eu