PhD Position in Biomolecular NMR and Artificial Intelligence

European Commission; France; Sur place; EUR 40 000 - 60 000; Plein temps

Résumé du poste

The European Commission offers a 3-year PhD position at École Normale Supérieure, focusing on structural biology and NMR techniques. The candidate will receive comprehensive training while contributing to groundbreaking research on protein dynamics and developing analytical methods using AI. This opportunity is ideal for those with a Master's degree and a keen interest in computational biology.

Qualifications

• Master's degree required.
• Programming experience in Python preferred.
• Strong interest in computational methods.

Responsabilités

• Develop and apply novel NMR techniques.
• Contribute to AI-driven NMR data analysis.
• Enhance computational tools for exchange NMR data simulation.

Connaissances

Computational methods

Programming in Python

Interest in structural biology

Formation

Master's degree in chemistry, biophysics, physics, or computer science

Description du poste

Chemistry » Reaction mechanisms and dynamics

Chemistry » Analytical chemistry

Computer science » Modelling tools

Physics » Chemical physics

Physics » Computational physics

Organisation/Company École Normale Supérieure Department Chemistry Department Research Field Chemistry » Physical chemistry Chemistry » Reaction mechanisms and dynamics Chemistry » Analytical chemistry Computer science » Modelling tools Physics » Biophysics Physics » Chemical physics Physics » Computational physics Researcher Profile First Stage Researcher (R1) Positions PhD Positions Country France Application Deadline 15 Aug 2025 - 00:00 (Europe/Paris) Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No

Offer Description

Position Summary

A fully funded 3-year PhD position is available in the group of Guillaume Bouvignies at theChimie Physique Chimie du Vivant (CPCV – UMR 8228), based at the prestigiousÉcole Normale Supérieure (ENS)in the heart of Paris. This is an exciting opportunity for a motivated student to work at the intersection of structural biology, physical chemistry, and computational science. The PhD project aims to decipher the complex energy landscapes of proteins at atomic resolution. This will be achieved by developing and integrating novel Nuclear Magnetic Resonance (NMR) techniques with cutting-edge artificial intelligence tools. The research will focus on characterizing sparsely populated, transiently formed protein states, which are essential for understanding biological function and for designing new therapeutic interventions.

PhD Project Focus

The successful candidate will receive comprehensive training and will contribute to several high-impact research areas, including:

• Advanced NMR Method Development: Learning and applying novel CEST NMR experiments (e.g., multi-site DANTE-based CEST) to probe protein dynamics on micro- to millisecond timescales.
• AI for Scientific Analysis: Developing and training deep learning algorithms to automate and accelerate the analysis of complex, multi-state NMR data.
• Computational Tool Enhancement: Contributing to the development of ChemEx, a Python-based software for simulating and analyzing exchange NMR data.
• Application to a Key Biological System: Contributing to a collaborative project on the human HSP90 protein by supporting experimental design and performing advanced data analysis.

Start Date

The position is available from Fall 2025. Please note that the precise start date is flexible (Fall 2025 or early 2026) and will be determined in accordance with the university's mandatory administrative validation timeline for research personnel.

Candidate Profile

We are looking for enthusiastic and curious candidates who:

• Hold or are about to complete a Master's degree in chemistry, biophysics, physics, computer science, or a related field.
• Possess a strong interest in computational methods and their application to challenging problems in structural biology.
• Have some programming experience, preferably in Python, or a strong motivation to learn.
• Are excited to work both independently and as part of a collaborative, interdisciplinary team.

Prior experience in biomolecular NMR or machine learning is an advantage but is not required. Comprehensive training in all aspects of the project will be provided.

Scientific Environment

The research group is part of a world-class, interdisciplinary environment with access to state-of-the-art NMR facilities, including spectrometers at 500, 600, 800, and soon 900 MHz, with regular access to ultra-high-field NMR instrumentation (up to 1.2 GHz) through the Infranalytics infrastructure. The project offers a unique opportunity to gain expertise in both experimental and computational biophysics.

Application Procedure

Applicants should submit the following documents as a single PDF file:

• A cover letter describing your research interests and motivation for pursuing a PhD in this field.
• University transcripts (Master's and Bachelor's degrees).
• Contact details for two referees (who may be contacted for reference letters).
• Yuwen T., Kay L.E., Bouvignies G. Dramatic Decrease in CEST Measurement Times Using Multi-Site Excitation . ChemPhysChem (2018) 19, 1707–1710. DOI
• Vallurupalli P., Bouvignies G., Kay L.E. Studying "invisible" excited protein states in slow exchange with a major state conformation . JACS (2012) 134, 8148–8161. DOI
• Bouvignies G. et al. Solution structure of a minor and transiently formed state of a T4 lysozyme mutant . Nature (2011) 477, 111–114. DOI

Where to apply

E-mail [e-mail]

Requirements

Research Field Chemistry Education Level Master Degree or equivalent

Research Field Physics Education Level Master Degree or equivalent

Research Field Computer science Education Level PhD or equivalent

Languages ENGLISH Level Excellent

Research Field Chemistry » Physical chemistryChemistry » Reaction mechanisms and dynamicsChemistry » Analytical chemistryComputer science » Modelling toolsPhysics » Chemical physicsPhysics » BiophysicsPhysics » Computational physics