Postdoctoral Scientist

**11 days left to apply**

**About BioMed X**:
Through its XSeed Labs model, BioMed X embeds independent research teams within the R&D environments of industry partners, enabling close scientific interaction while maintaining academic independence. Together with our partners, we identify big biomedical research challenges and provide creative solutions by combining global crowdsourcing with local incubation of the world’s brightest early-career research talents. Each of the highly diverse research teams at BioMed X has access to state-of-the-art research infrastructure and is continuously guided by experienced mentors from academia and industry. At BioMed X, we combine the best of two worlds - academia and industry - and enable breakthrough innovation by making biomedical research more efficient, more agile, and more fun.

**About Team ADB**:
Team ADB is a newly established research team within BioMed X’s XSeed Labs program. The team will develop a predictive, AI-enabled platform for the rational design of bispecific antibodies, addressing key limitations such as steric hindrance, epitope accessibility, spatial dynamics, and physiological constraints that currently limit the systematic development of immune cell engagers (ICEs) and dual-targeting antibody-drug conjugates (ADCs). In close collaboration with Servier, the team operates at the interface of academia and industry, translating advances in antibody engineering, structural biology, and machine learning into geometry-aware design strategies with high translational relevance. The team will be based on Servier’s R&D campus in Paris-Saclay, near Paris, France, enabling close, day-to-day interaction with industry scientists.

**The Position**:
We are looking for a talented and intellectually curious Research Scientist with deep computational expertise and hands-on engineering skills to play a key role in designing and developing the core AI/ML algorithms and computational architecture of our platform.
- A PhD (or equivalent experience) in Computer Science, Artificial Intelligence, Machine Learning, Applied Mathematics, Computational Biology, or a related field.
- Strong experience in machine learning and deep learning, including AI model and algorithm development.
- Experience with neural network architectures (e.g. Transformers and Graph Convolutional Networks) and large-scale representation learning.
- Strong programming skills in Python or R for data analysis and statistical workflows.
- Ability to translate open-ended scientific questions into computational strategies, data management plans, and reproducible ML workflows.

**Key Responsibilities**:
In this role, you will:

- Design and implement AI/ML architectures addressing spatial and structural challenges in bispecific antibody design.
- Develop and maintain robust ML pipelines, including data management, data analysis, model training, evaluation and benchmarking.
- Contribute to the development of a scalable AI platform integrating biological insight with modern ML approaches (deep learning, neural networks, foundation models)
- Collaborate closely with experimental scientists and industry stakeholders to translate computational innovations into biologically and therapeutically meaningful outcomes.

**Required Skills**:
Scientific & Computational Skills:

- Machine learning and deep learning expertise.
- Proficiency in modern deep learning frameworks (e.g., PyTorch, PyTorch Lightning).
- Experience handling large, heterogeneous datasets.
- Hands-on experience with GPU clusters, HPC environments, and large-scale ML experimentation.
- Practical experience with cloud services such as AWS, GCP, or Azure.
- Strong working knowledge of GitOps and MLOps platforms (e.g., GitHub, MLflow) and collaborative code development practices (code review, issue tracking, CI).
- Ability to reason about geometry, steric constraints, and structure-function relationships.
- Autonomy in installing, configuring, and maintaining software, packages, and computational environments, including GPU-enabled systems and ML frameworks.

Collaboration Skills:

- Strong analytical thinking and problem-solving; ability to translate open-ended biological questions into computational tasks.
- Strong communication skills and ability to collaborate in an interdisciplinary, international team.

**Additional skills (Nice to Have)**:

- Familiarity with 3D structural data (protein structures, molecular complexes) and spatial representations.
- Ability to interpret model outputs in a biological/biophysical context

**What We Offer**:

- The position is fully funded through a strategic industry partnership with Servier, offering a well-resourced research position starting **March 1, 2026 (negotiable).**:

- The position is offered as a fixed-term contract (CDD) in accordance with French labour law, initially limited for 3 years, with the possibility of an additional 2-year extension.
- Access to a high-level scientific and innovation ecosy