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 recruiting a Research Assistant (Bioinformatics) to support the development of an AI-enabled platform for the rational design of mono- and bispecific antibodies in immuno-oncology. This position is well-suited for early-career scientists with a strong interest in computational biology, protein science, and data-driven approaches to antibody design, who are motivated to develop skills toward AI and machine learning–based research. The Research Assistant will contribute to the computational analysis, annotation, and integration of protein- and antibody-related data, working closely with AI/ML scientists, structural biologists, and experimental collaborators. The role allows for increasing scientific autonomy over time, including the opportunity to contribute to methodological development and exploratory modeling approaches. The role focuses on bridging biological understanding with computational modeling, translating biological constraints into model-ready representations that support iterative design and prioritization of antibody constructs. The position offers a structured and supportive research environment at the interface of bioinformatics, protein science, and AI-assisted discovery, with strong mentoring and exposure to both academic and industry-driven research.
The Ideal Candidate Will Have
A Master’s degree (or equivalent) in Bioinformatics, Computational Biology, Molecular Biology, Biotechnology, Biochemistry, or a related field.
The ability to work in a structured, mentored research environment, benefiting from close interaction with senior scientists and industry partners.
Experience contributing to computational research projects that extend beyond routine data analysis (e.g. pipelines, models, or exploratory frameworks).
Key Responsibilities
In This Role, You Will
Support the analysis, curation, and organization of protein and antibody-related datasets, including sequence, structural, and functional information.
Contribute to data preparation and feature extraction for AI/ML–based antibody design workflows.
Assist in integrating biological and immunological context into computational models and design assumptions.
Help interpret computational predictions in light of basic structure–function relationships in antibodies.
Collaborate closely with AI/ML scientists, structural biologists, and experimental teams to ensure biological relevance and consistency of computational outputs.
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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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