Position description :

The newly opened Ricci Lab at Institut Imagine in Paris, one of Europe’s top biological research centers, is seeking a Ph.D. student to work on data-driven dynamical systems modeling of genetic disease. Our lab’s main goal is to build models which predict how biological systems (gene regulatory networks, cells, tissues) evolve in time and to understand how to intervene in these systems to minimize the health impact of complex genetic diseases.

Located in the heart of Paris, our lab welcomes candidates with strong backgrounds in applied mathematics, physics, computer science, or computational biology, and with experience working with biological data. As a member of our lab, you will have access to world-class computational and biological resources, including a state-of-the-art NVIDIA DGX H200 cluster and extensive in-house biological datasets. The successful candidate will have the opportunity to co-design new research directions with the PI. Current projects include:

• Data-driven optimal control of gene regulatory networks ;

• Morphogenetic modeling of whole tissue development, particularly in brain disease contexts.

The Ph.D. student is encouraged to pursue research at the intersection of machine learning, biology, and genetic disease modeling.

Resources :

• Compute : 12PB PureStorage (Flash) cluster, 8x NVIDIA DGX H200, 150TB PureStorage FlashBlade S scratch space, and 16–20 CPU nodes ;

• Data : Large, growing in-house omics datasets (scRNA-seq, spatial transcriptomics, pro teomics, ATAC-seq, etc.) ;

• Collaboration : Close integration with top institutions like Institut Pasteur, PR[AI]RIE, Institut Necker, and others ;

• Housing and quality-of-life : Reserved apartments near the Institut and subsidized travel.

Requirements :

Essential :

• Undergraduate degree in applied/pure mathematics, computer science, physics, compu tational biology, or related field ;

• Previous experience working with biological data ;

• Strong programming skills ;

• Proficiency in English (spoken and written).

It is preferred that the candidate will have experience with some of the following :

• Deep learning frameworks (transformers, diffusion models, neural ODEs/PDEs, CNNs) ;

• Dynamical systems and differential equations (especially data-driven models like SINDy, Koopman methods) ;

• Analysis of omics data (especially scRNA-seq, spatial transcriptomics) ;

• Using or fine-tuning foundation models.

Employment details :

• Monthly gross salary : €2454 ;

• Contract : Three years (until completion of thesis) ;

• Work time : 37.5 hours/week ;

• Benefits : 60% healthcare coverage, 75% transport reimbursement, €100/month in restaurant vouchers (60% covered).

Application :

Please send a CV, contact information for two references, and a brief description of relevant coursework and/or research experience (∼ 1 page)