DESCRIPTION :
This postdoc position is funded for two years by the grant from Programme Inria Quadrant (PIQ). The main goal is to develop a graph neural network architecture to investigate conformational dynamics of macromolecular complexes. The Postdoc researcher will be in connection with Yasaman Karami (Chargee de recherche, Inria) with expertise in proteins conformational dynamics and allostery, and will be hosted in the Delta team within the Inria center at the Universite de Lorraine. Our team consists of two permanent researchers with several PhD and postdoc members, and is expected to grow by hiring new members. It provides a multidisciplinary and international environment, and benefits from experts in structural bioinformatics, as well as in computer science and deep learning. Our main goal is to develop deep learning models, to study, and predict protein structure, interactions, function and to further design synthetic molecules. The team has access to computational resources, including
efficient GPUs and CPUs, from different cluster centers including Grid5000, Jean Zay, etc.
Mission confiée
Biomolecules such as proteins and nucleic acids are at the heart of virtually all fundamental cellular processes. They adopt complex dynamic behavior and their functions are directly linked to the arrangement of atoms in 3D and dynamics. Therefore, characterizing the structure, dynamics and conformational changes of biomolecules can help understand the molecular mechanisms of underlying diseases. We recently developed ComPASS, a large-scale computational method designed to study communication networks in protein-protein and protein-nucleic acid complexes [1]. ComPASS has been applied to different biological systems, facilitating the interpretation of the conformational dynamics. In a recent study, we highlighted the role of cysteine hyperoxidation in Nucleosome [2,3]. Moreover, we took major steps in learning conformational dynamics by proposing DynamicGT, a novel architecture that combines cooperative graph neural networks with a graph transformer, to predict binding
sites [4].
The main goal of this Postdoc is to elucidate the conformational dynamics of macromolecular complexes and to develop a method for understanding their communications. The main idea is to take another major step, taking advantage of the recent developments of AI and propose a novel approach to uncover distinct mechanisms in macromolecular systems. The post-doctoral researcher will also help supervise the team's students working on computational biology problems.
[1] Bheemireddy S, Gonzalez-Aleman R, Bignon E, Karami Y. Communication pathway analysis within proteinnucleic acid complexes. bioRxiv, 2025.
[2] Karami Y, Bignon E. Cysteine hyperoxidation rewires communication pathways in the nucleosome and destabilizes the dyad. Computational and Structural Biotechnology Journal, 2024, 23, 1387-1396.
[3] Karami Y, Gonzalez-Aleman R, Duch M, Qiu Y, Kedjar Y, Bignon E. Histone H3 as a redox switch in the nucleosome core particle: insights from molecular modeling. bioRxiv, 2024.
[4] Mokhtari O, Grudinin S, Karami Y, Khakzad H. DynamicGT: a dynamic-aware geometric transformer model to predict protein binding interfaces in flexible and disordered regions. bioRxiv, 2025.
Principales activités
1. Implementing the deep learning architecture
2. Contributing into training data collection and curation
3. Validating the method and analysing the results over SOTA benchmarks
4. Supervising Master students and teamwork with PhD students, collaborating with other teams
5. Writing scientific articles, software development and participating in international conferences
Code d'emploi : Spécialiste Virologie (h/f)
Domaine professionnel actuel : Chercheurs et Analystes
Niveau de formation : Bac+8
Temps partiel / Temps plein : Plein temps
Type de contrat : Contrat à durée indéterminée (CDI)
Compétences : Données d'Apprentissage, Intelligence Artificielle, Réseaux de Neurones Artificiels, Bio-Informatique, Biologie Computationnelle, Python (Langage de Programmation), Molecular Modelling, Conception et Développement de Logiciel, Graphics Processing Unit (GPU), Pytorch, Deep Learning, Technologies Informatiques, Anglais, Sens de la Communication, Esprit d'Équipe, Motivation Personnelle, Architecture, Télécommunications, Biochimie, Biotechnologies, Systèmes Biologiques, Cryptographie, Organisation d'Événements, Biologie Moléculaire et Cellulaire, Approche Pluridisciplinaire, Recherche Post-Doctorale, Séquençage ARN, Documentation Scientifique, Curation, Protéines, Management d'Équipe
Courriel :
yasaman.karami@inria.fr
Téléphone :
0139635511
Type d'annonceur : Employeur direct
