General information
Offer title : Two Postdoctoral (M/F) Positions in the Development of Machine Learning Methods for Single-Cell Multi-Omics Spatiotemporal Data (H/F)
Reference : UMR3738-DEBPHI-004
Number of position : 2
Workplace : PARIS 15
Date of publication : 17 January 2026
Type of Contract : Researcher in FTC
Contract Period : 12 months
Expected date of employment : 1 March 2026
Proportion of work : Full Time
Remuneration : 3 131.32€ and 4 806.76€ gross monthly based on experience
Desired level of education : Doctorate
Experience required : Indifferent
Section(s) CN : 51 - Modélisation mathématique, informatique et physique pour les sciences du vivant
Missions
Single-cell high-throughput sequencing technologies generate unprecedented volumes of molecular data at cellular resolution, opening new avenues for the application of machine learning to fundamental biological problems. The postdoctoral researchers will be recruited to join the Machine Learning for Integrative genomics team at Institut Pasteur in the context of the ERC Starting Grant MULTI-viewCELL.
One position will focus on the development of multi-modal Foundation Models that integrate single-cell omics with spatiotemporal information. The second position will address the development of a virtual tissue model, exploiting spatial transcriptomics data and network-theoretic approaches.
Activities
- design of a new mathematical method
- monitoring and study of publications relevant to the field
- programming/coding in Python (Pytorch)
- presentation of results at conferences
- interaction with team members and international collaborators
Skills
Degree : PhD in computer science, machine learning, or computational biology
We expect a candidate with a strong background in machine learning or statistics. The candidate must also be proficient in high-level languages like Python. Familiarity with single-cell date and experience with existing single-cell methods and software would represent a strong advantage. Excellent communication skills and team spirit, and an ability to work in autonomy are essential. Fluent English both spoken and written is required.
Work Context
The Machine Learning for Integrative Genomics team (https://research.pasteur.fr/en/team/machine-learning-for-integrative- genomics/) at Institut Pasteur, led by Laura Cantini, works at the interface of machine learning and biology (tools developed by the team: https://github.com/cantinilab). The team is composed of 9 people : 4PhD students, 3 post doc, 1 research engineer and 1 assistant. The team is associated with the Institut Pasteur's Computational Biology Department, UMR3738 and the PRAIRIE Artificial Intelligence Institute. The team recently won ERC StG funding, which is the subject of this recruitment. The postdoctoral researchers recruited will be under Laura Cantini's hierarchical authority.
Constraints and risks
Work on computer
Additional Information
https://www.ins2i.cnrs.fr/fr/cnrsinfo/laura-cantini-un-projet-erc-starting-grant-linterface-entre-apprentissage-automatique-et
https://research.pasteur.fr/en/project/multi-viewcell/