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 seeking a Postdoctoral Research Scientist in Computational Structural Biology to shape the structure-guided, geometry-aware, and physics-informed layer of an AI-empowered bispecific antibody design platform. This role is suited for scientists motivated by protein structure, molecular dynamics, and spatial constraints, and who enjoy working at the interface of structural biology, biophysics, and data-driven modeling. The successful candidate will bring physical realism to antibody design by applying structure-guided computational biophysics methods, including molecular dynamics, to model antibody–antigen interactions, epitope accessibility, and multi-target binding geometries under biologically relevant constraints, including membrane proximity and immune synapse formation. Working closely with AI/ML scientists, antibody engineers, immunologists, and industry partners, the postdoc will translate AI-derived epitope predictions into biophysically plausible and experimentally testable antibody configurations, with a focus on bispecific and multispecific formats.
This position contributes directly to establishing a predictive, geometry- and mechanism-aware framework for bispecific antibody discovery, shaping an integrated, next-generation approach with direct relevance for the development of immune-based therapeutics.
The Ideal Candidate Will Have
A PhD in Computational Structural Biology, Computational Chemistry, Biophysics, Biochemistry, or a closely related field
A track record of peer-reviewed scientific publications in computational structural biology, biophysics, or related biomolecular modeling fields
Demonstrated experience applying structure-guided computational methods to complex biomolecular systems
The ability to work effectively in interdisciplinary and international research teams
Key Responsibilities
In This Role, You Will
Develop and apply structure- and physics-based models to evaluate antibody–antigen interactions, epitope accessibility, and steric feasibility across mono- and bispecific formats.
Translate AI-derived predictions into biophysically plausible binding geometries using docking and molecular dynamics approaches.
Characterize conformational flexibility and spatial constraints relevant to multi-target antibody binding.
Extract and formalize geometric descriptors from structural ensembles to support downstream modeling.
Provide structural and biophysical insight to crit
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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