Two Postdoctoral Positions: The Institut Pasteur is inviting applications for two postdoctoral positions focused on developing machine learning methods for single-cell multi-omics spatiotemporal data. The successful candidates will work within the Machine Learning for Integrative Genomics team.
Two Postdoctoral Positions in Machine Learning for Single-Cell Multi-Omics
Designation
Postdoctoral Researcher (2 Positions)
Table
| Detail | Information |
|---|---|
| Reference | UMR3738-DEBPHI-004 |
| Number of Positions | 2 |
| Contract Type | Researcher in FTC |
| Contract Period | 12 months |
| Expected Start Date | 1 March 2026 |
| Work Proportion | Full-Time |
| Remuneration | €3,131.32 to €4,806.76 gross monthly based on experience |
| Location | Paris 15 |
| Application Deadline | 7 February 2026, 23:59 (Paris Time) |
Research Area
Machine Learning for Integrative Genomics, focusing on single-cell omics technology and spatiotemporal data integration.
Location
Institut Pasteur, Paris, France
Eligibility/Qualification
- Degree: PhD in computer science, machine learning, or computational biology.
- Experience: Indifferent, but a strong background in machine learning or statistics is desired.
- Skills: Proficient in high-level languages like Python; familiarity with single-cell data and methods is advantageous; excellent communication skills and ability to work independently; fluent in English (spoken and written).
Job Description
Postdoctoral researchers will:
- Develop new mathematical methods.
- Stay updated on relevant publications in the field.
- Program/code in Python using PyTorch.
- Present results at conferences.
- Collaborate with team members and international researchers.
How to Apply
Ensure your candidate profile is accurate before applying through the application portal on the Institut Pasteur website. Applications should be submitted electronically.
Last Date for Apply
7 February 2026, 23:59 (Paris Time)
For more information, please visit the Machine Learning for Integrative Genomics team and MULTI-viewCELL project.
