Post-doc position in deep learning for genomics, Paris, France

European Commission; France; Sur place; EUR 30 000 - 45 000; Plein temps

Résumé du poste

Join the Computational and Quantitative Biology Lab at Sorbonne University as a Post-doctoral researcher. Work on an ERC-funded project focused on proteome diversification in evolution, employing cutting-edge AI techniques. Collaborate with a dynamic team of scientists, leveraging your programming expertise to drive innovative biological research for two years. A fully funded position with competitive salary and opportunities for international collaboration.

Prestations

Fully funded position for 2 years

Collaboration with international researchers

Flexible start date

Qualifications

• Seeking an enthusiastic and highly motivated scientist.
• Strong programming skills and basic biological knowledge required.
• Excellent command of English, both oral and written.

Responsabilités

• Involved in deep learning development and application.
• Data collection and curation, framework management.
• Collaboration with interdisciplinary teams.

Connaissances

Programming skills

Basic biological knowledge

Natural Language Processing

Geometric Deep Learning techniques

Management systems for computational workflows

Knowledge about protein sequences and structures

Interpersonal skills

English communication

Formation

PhD or equivalent

Description du poste

Organisation/Company Sorbonne University Research Field Computer science » Programming Biological sciences Mathematics » Applied mathematics Researcher Profile Recognised Researcher (R2) Positions Postdoc Positions Country France Application Deadline 31 Jul 2025 - 23:59 (Europe/Paris) Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Horizon 2020 Is the Job related to staff position within a Research Infrastructure? No

Offer Description

The Computational and Quantitative Biology Lab at Sorbonne University in Paris has an opening for aPost-doctoral researcherto join E. Laine's team in an ERC-funded project to explore proteome diversification in evolution.

Our team focuses on the fascinating diversity of proteins. More specifically, the different protein versions or isoforms that can be produced from a single gene. How this diversity emerged and expanded in evolution, how it impacted complex behavioural traits such as vocal learning in humans and songbirds.

You will join an interdisciplinary and highly collaborative team. You will work alongside highly motivated scientists passionate about developing innovative computational and AI methods for understanding the fundamental mechanisms of life's machinery toward optimally guiding biological intervention.

Our ERC-funded project, PROMISE, aims at leveraging the landscape of protein isoforms across hundreds of millions of years of evolution with cutting-edge AI techniques to determine how proteins function and interact with one another in vivo.

You will have a pivotal role in the project, at the cross-talk of -omics data integration, deep learning development, and application to a concrete biological system. You will have the opportunity to get involved in data collection and curation, in the development of deep learning architectures, and their adaptation and deployment for downstream use cases, in interpretability assessment and uncertainty quantification, and in database and online services set up and management. You will coordinate the building of a robust and maintainable framework for sharing the codes and data of the project.

You will work in close collaboration with E. Laine (http://www.lcqb.upmc.fr/laine/ ), Associate Professor at Sorbonne University, S. Grudinin, researcher at the Jean Kunzmann Lab (Grenoble, France), and H. Richard, researcher at the Robert Koch Institute (Berlin, Germany).

Funding

The position is fully funded for 2 years. The team benefits from excellent support thanks to an ERC Consolidator Grant. Salary will be commensurate to experience following Sorbonne University's pay scale. Start date is flexible but no longer than December 2025.

The team provides its members with many opportunities to collaborate with and receive feedback from an inter-disciplinary collaborative network of international researchers from complementary backgrounds and to take part in international community efforts.

Apply: Send a motivation letter with your CV and the contact information of minimum two references to Elodie Laine: [e-mail] .Latest deadline for applications is 31 July 2025.

Where to apply

E-mail [e-mail]

Requirements

Research Field Computer science Education Level PhD or equivalent

Skills/Qualifications

We are seeking an enthusiastic and highly motivated scientist with strong programming skills, basic biological knowledge, and a very developed taste for AI, data, and code standards as well as web technologies. The following skills will be an advantage:

• Knowledge and know-how in Natural Language Processing or Geometric Deep Learning techniques
• Prior experience in management systems for computational workflows
• Knowledge about protein sequences and structures
• Ability and taste for interacting with people from different backgrounds
• First-rate oral and written English communication capabilities.

Languages ENGLISH Level Excellent

Research Field Computer science » ProgrammingBiological sciencesMathematics » Applied mathematics