Role overview
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.
What you'll work on
- 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.
What we're looking for
- Familiarity with 3D structural data (protein structures, molecular complexes) and spatial representations.
- Ability to interpret model outputs in a biological/biophysical context
Interview 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-J01
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