Research Assistant– Bioinformatics (m/f/d)

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.
• Document analyses and contribute to internal reports, figures, and presentations supporting iterative design cycles.

Required Skills

• Foundational knowledge of proteins and basic antibody biology.
• Strong interest in computational analysis and data-driven research.
• Good experience with programming or data analysis (e.g., Python, R, or similar).
• Motivation to learn and apply AI/ML concepts in the context of protein and antibody design.
• Ability to work effectively in an interdisciplinary and international research environment.
• Clear scientific communication skills and openness to feedback and mentoring.

Additional skills (Nice to Have)

• Exposure to protein sequence or structural data (e.g., PDB, UniProt, sequence analysis).
• Experience with machine learning, statistics, or computational modeling.
• Familiarity with basic concepts in immunology or immuno-oncology.
• Experience contributing to a computational or bioinformatics research project.

What We Offer

• A fully funded research position within a high-profile BioMed X XSeed Labs project in collaboration with Servier.
• A fixed-term contract (CDD) under French labour law, initially for up to 3 years, with the possibility of extension.
• A strong mentoring and training environment, with close interaction with senior scientists in AI/ML, structural biology, and antibody research.
• Direct exposure to AI-enabled antibody discovery workflows at the academia–industry interface.
• Opportunities to contribute to scientific publications and conference presentations, aligned with project objectives and confidentiality requirements.
• An international, diverse, and collaborative work environment based on Servier’s R&D campus in Paris-Saclay.
• A role that provides excellent preparation for doctoral studies or computational careers in biomedical research.

Application Process

Applications will be reviewed on a rolling basis. For full consideration, please apply by 15 February 2026. Please submit your application via our online application system: https://career.bmedx.com/job/2026-PAR-J03

Your application should include:

• A one-page cover letter describing your motivation and suitability for the position.
• A curriculum vitae outlining your scientific background, research interests, and publication record.
• Two references will be requested at a later stage as part of the interview process.

At BioMed X, we embrace diversity as a key driver of innovation. We are committed to equal opportunity in employment for all employees and applicants, without regard to race, color, religion, ideology, sex, sexual orientation, age, gender identity or expression, national origin, or disability.

For informal inquiries, please contact: BioMed X Institute, Im Neuenheimer Feld 515, 69120 Heidelberg, Germany

For questions: adjobimey@bmedx.com or spal@bmedx.com

To read about us: https://bmedx.com