BioMed X Institute

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 companies and conducted by early-career scientists recruited from the best schools around the world. The combination of global crowdsourcing with local incubation of the best research talents and ideas allows us to solve the biggest challenges in biomedical research.

Listed Jobs

Company Name

BioMed X Institute

Job Title

Postdoctoral Scientist - AI/ML Engineer (m/f/d)

Job Description

**Job Title:** Postdoctoral Scientist – AI/ML Engineer **Role Summary:** Lead the design and development of core AI/ML algorithms and computational architecture for a predictive, geometry‑aware platform targeting bispecific antibody design. Serve as the technical ML lead, translating complex scientific questions into reproducible, scalable models and pipelines while collaborating closely with structural biology, immunology, bioinformatics, and industry partners. **Expectations:** - Create and refine advanced AI/ML models (deep learning, transformer‑based, graph neural networks) for spatial and structural challenges in antibody engineering. - Build and maintain end‑to‑end ML pipelines that are robust, reproducible, and ready for platform deployment. - Bridge computational work with experimental validation, delivering biologically meaningful results. - Operate autonomously while contributing to a multidisciplinary team and aligning with industry‑partner goals. **Key Responsibilities:** - Design and implement AI/ML architectures addressing steric hindrance, epitope accessibility, and spatial dynamics of bispecific antibodies. - Develop scalable data‑management and preprocessing workflows for heterogeneous biological datasets. - Train, evaluate, and benchmark models, integrating foundation models and representation learning techniques. - Maintain version‑controlled codebases and documentation to ensure reproducibility. - Collaborate with experimental scientists and industry stakeholders to iteratively improve model performance and therapeutic relevance. - Contribute to the overall AI platform architecture, ensuring modularity and scalability for future extensions. **Required Skills:** - Proven expertise in machine learning and deep learning, including model/algorithm development. - Hands‑on experience with neural network architectures such as Transformers and Graph Convolutional/Graph Neural Networks. - Strong programming proficiency in Python (preferred) or R for data analysis, model implementation, and workflow automation. - Ability to design reproducible ML pipelines, manage large‑scale heterogeneous datasets, and perform rigorous model evaluation. - Excellent problem‑solving skills to convert open‑ended scientific questions into computational strategies. - Effective communication and teamwork skills for interdisciplinary collaboration. **Required Education & Certifications:** - PhD (or equivalent experience) in Computer Science, Artificial Intelligence, Machine Learning, Applied Mathematics, Computational Biology, or a closely related discipline. - No additional certifications required; demonstrated research and engineering experience in relevant fields is essential.

Gif-sur-yvette, France

On site

05-02-2026

Company Name

BioMed X Institute

Job Title

Postdoctoral Scientist – Computational Structural Biology (m/f/d)

Job Description

Job title: Postdoctoral Scientist – Computational Structural Biology Role Summary: Postdoctoral researcher responsible for incorporating physics‑based and structure‐guided computational methods into an AI-driven platform for bispecific antibody design. Focus on modeling antibody–antigen interactions, epitope accessibility, steric feasibility, and multi‑target binding geometries, and translating AI predictions into experimentally testable designs. Expectations: - Advance predictive framework for bispecific antibody discovery. - Collaborate with AI/ML scientists, antibody engineers, immunologists, and industry partners. - Publish scientific findings in peer‑reviewed journals. Key Responsibilities: - Develop and apply structure‑ and physics‑based models for evaluating antibody‑antigen interactions and epitope accessibility in mono‑ and bispecific formats. - Translate AI‑derived epitope predictions into biophysically plausible binding geometries using docking and molecular dynamics. - Characterize conformational flexibility and spatial constraints relevant to multi‑target antibody binding and immune synapse formation. - Extract and formalize geometric descriptors from structural ensembles to support downstream modeling. - Provide structural and biophysical insights to guide antibody engineering and experimental validation. Required Skills: - Proficiency in molecular dynamics simulations, docking, and structure‑based modeling (Python, C++, GROMACS/AMBER, or equivalent). - Strong analytical and quantitative skills for evaluating conformational landscapes and steric feasibility. - Ability to interpret and incorporate AI‑generated epitope predictions into biophysical models. - Experience working with bispecific or multispecific antibody formats and understanding of relevant biophysical constraints. - Excellent communication skills for interdisciplinary collaboration and publication writing. Required Education & Certifications: - PhD in Computational Structural Biology, Computational Chemistry, Biophysics, Biochemistry, or closely related field. - Peer‑reviewed publications demonstrating expertise in computational structural biology or biomolecular modeling.

Gif-sur-yvette, France

On site

05-02-2026

Company Name

BioMed X Institute

Job Title

Research Assistant – Immunology (m/f/d)

Job Description

Job title: Research Assistant – Immunology Role Summary: Support functional evaluation and data‑driven optimization of immuno‑oncology mono‑ and bispecific antibodies, linking quantitative immunological readouts with structure‑ and AI‑guided design. Work at the interface of experimental biology, computational modeling, and industry collaboration to validate and refine antibody constructs for therapeutic activity. Expectations: Deliver accurate, reproducible experimental data; integrate computational predictions with immunological assays; iterate design–validation cycles; collaborate effectively across multidisciplinary teams and industry partners; maintain rigorous data quality and documentation. Key Responsibilities: - Perform functional assays for T‑cell activation, cytokine release, and cytotoxicity against tumor targets using cell‑based systems. - Compare performance of mono‑ and bispecific antibody candidates, generating quantitative metrics of immune engagement and tumor cell killing. - Apply computational predictions and immunological constraints to prioritize antibody designs, contributing experimental feedback to design loops. - Analyze assay data, generate statistical reports, and present findings to senior scientists and cross‑disciplinary collaborators. - Ensure experimental rigor, maintain detailed records, and adhere to biosafety and quality standards. Required Skills: - Practical experience in cell‑based immunological assays (e.g., T‑cell activation, cytotoxicity, flow cytometry). - Understanding of antibody formats, bispecific antibody engineering, and immuno‑oncology concepts. - Ability to interpret and apply computational predictions to experimental workflows. - Strong analytical, data‑processing, and quantitative skills. - Effective written and verbal communication in an interdisciplinary setting. - Team‑oriented mindset, curiosity, and a willingness to learn. Required Education & Certifications: - M.Sc. (or equivalent) in Computational Immunology, Molecular Biology, Antibody Design, Protein Engineering, or related discipline.

Gif-sur-yvette, France

On site

05-02-2026

Company Name

BioMed X Institute

Job Title

Research Assistant– Bioinformatics (m/f/d)

Job Description

Job title: Research Assistant – Bioinformatics (m/f/d) Role Summary: Supports the development of an AI-enabled platform for rational design of mono‑ and bispecific antibodies in immuno‑oncology. Performs computational analysis, data curation, and feature extraction to enable machine‑learning workflows, bridging biological context with computational models. Expactations: - Deliver accurate, reproducible datasets for antibody design pipelines. - Translate biological constraints into model‑ready representations. - Collaborate effectively with AI/ML scientists, structural biologists, and experimentalists. - Progress towards independent contribution to methodological development and exploratory modeling. Key Responsibilities: - Curate and organize protein/antibody sequences, structures, and functional annotations. - Prepare data and extract features for AI/ML antibody design workflows. - Integrate immunological and structural context into computational models. - Interpret model outputs in light of antibody structure‑function relationships. - Collaborate with cross‑disciplinary teams to ensure biological relevance of computational results. Required Skills: - Proficiency in scripting languages (Python, R) for data manipulation and analysis. - Experience with bioinformatics tools (BLAST, Pfam, PDB mining, etc.). - Familiarity with machine‑learning frameworks (scikit‑learn, TensorFlow, PyTorch). - Strong analytical mindset and ability to develop computational pipelines. - Effective communication of complex computational results to biologists and engineers. Required Education & Certifications: - Master’s degree or equivalent in Bioinformatics, Computational Biology, Molecular Biology, Biotechnology, Biochemistry, or related field.

Gif-sur-yvette, France

On site

05-02-2026