Postdoctoral Fellow In Systems Biology H/F Servier

Who are we? 22,000 passionate individuals from over 50 nationalities, driven by an entrepreneurial spirit. Every day, we move forward with and for patients, with and for our teams, motivated by the desire to care, to dare, to grow, and to commit to being useful to those in need.

Come and experience and contribute to our commitment #MovedByYou.

www.servier.com

Are you a highly motivated researcher passionate about the quantitative design of next-generation therapeutics? We are seeking a Postdoctoral Fellow to join our interdisciplinary research program focused on the characterization, modeling, and design of multispecific antibodies, including antibody-drug conjugates and T-cell engagers. This is a unique opportunity to play a crucial role in developing multi-scale predictive models and active-learning pipelines that iteratively guide the engineering of novel therapeutic candidates.

Why Join Us?

- Impactful Research: Contribute to a mechanistic understanding of multispecific antibody binding (avidity) and function (internalization, T-cell activation). You will integrate mechanistic insights with quantitative assay readouts to help establish quantitative design rules for life-changing therapeutics.
- Innovative Environment: Drive efforts in mathematical modeling, biophysical data analysis, and machine learning for the optimization of therapeutic antibody properties. You will work with internal experimental datasets to build predictive computational frameworks grounded in real-world data.
- Collaborative Team: Work within the Data Sciences & Data Management Research Unit alongside AI/ML experts and computational biologists. You will interact closely with experimental teams and have the opportunity to collaborate with an emerging startup from the BioMed X initiative.

Responsibilities:

- Develop and implement mathematical and computational models to characterize antibody binding and function.
- Contribute to key scientific use cases in collaboration with experimental teams, translating biological questions into modeling strategies and guiding iterative experimental design.
- Perform rigorous quantitative analysis and parameter inference on biological and biophysical datasets (e.g., SPR, flow cytometry, functional assays) to extract mechanistic insights and inform data-driven decisions.
- Communicate progress and scientific insights through internal meetings, technical reports, and peer-reviewed publications.
- Collaborate across international sites, including regular travel between R&D in Saclay (France) and Symphogen in Ballerup (Denmark).

Profile:

- PhD in Applied Mathematics, Computational Biology, Biophysics, Physics, Bioengineering, Computer Science, or a related quantitative field.
- Strong experience in mathematical or computational modeling, including mechanistic or biophysical approaches (e.g., ODE-based, stochastic, or spatial models).
- Experience analyzing quantitative biological or biophysical data, including parameter estimation and statistical or Bayesian inference.
- Proficiency in Python and common scientific computing libraries; experience with machine-learning approaches is valued.
- Familiarity with ligand-receptor modeling and binding kinetics is highly valued; experience with developability or antibody design workflows is a plus.
- Experience with cloud computing or scalable computing environments (e.g., Google Cloud Platform) is desirable.
- Strong written and oral English communication skills, with the ability to communicate complex concepts clearly.

We are committed to equal opportunities and developing talents in all their diversity. We value both experience and the desire to engage daily in contributing to therapeutic progress for the benefit of patients. If this offer resonates with you, seize this opportunity to meet us!