Job Specifications
About BioMed X
BioMed X is a leading innovation hub for pharma. With our global network of research institutes at top universities and incubators within pharmaceutical companies, we bridge the gap between academia and industry. We are pioneers in applying the principles of design thinking and crowdsourcing to drug discovery and development. With our unique model, we identify key challenges across all therapeutic areas, recruit top academic talent, and co-create tailored solutions with our pharma partners. In our stimulating ecosystem, early-career researchers grow into future scientific leaders. They perform exploratory research, deliver industry-grade results, and pave the way to next-generation therapies. At BioMed X, we value curiosity, diversity, and purpose. Our goal is to serve as a vital catalyst for innovation in global health for the benefit of all patients.
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.
This role is best suited for candidates who are motivated by the design and refinement of advanced AI/ML models, including deep learning and transformer-based architectures. The ideal candidate enjoys working with complex, heterogeneous datasets, and collaborating closely with experimental scientists and industry partners to translate computational innovation into robust, reproducible research and platform-grade solutions. The role will contribute to our long-term ambition of enabling a predictive, geometry-aware paradigm for bispecific antibody design that can meaningfully impact how immune cell engagers and related biologics are discovered and optimized for therapeutic use. The AI/ML Postdoctoral Scientist serves as the technical lead for machine learning and platform development, working in close collaboration with structural biology, immunology, and bioinformatics team members.
The Ideal Candidate Will Have
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
About the Company
BioMed X is an independent research institute with sites in Heidelberg, Germany, New Haven, Connecticut, XSeed Labs in Ridgefield, Connecticut, and a worldwide network of partner locations. We operate at the interface between academia and industry, performing biomedical research and drug discovery & development in the fields of oncology, immunology, neuroscience, women’s health, cardiometabolic diseases, platform technologies, and artificial intelligence.
All our research projects are supported by leading pharmaceutical com...
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