Scientist – CAR Design
About Match Medicines
Match Medicines is a Munich-based biotech company developing next-generation, off-the-shelf T-cell therapies for the treatment of autoimmune diseases and T-cell–mediated malignancies. Our platform is built on selective HLA reduction and precision T-cell targeting, enabling the elimination of pathogenic T-cell clones while preserving healthy immune function.
We combine advanced cell engineering with AI-driven protein design to create highly selective, scalable, and rapidly deployable cell therapies. By integrating computational biology, structural modeling, and translational development, we are building a new class of precision immunotherapies.
The Role
We are seeking an exceptional Scientist to lead computational protein engineering efforts within our precision CAR-T program targeting pathogenic T-cell receptors (TCRs) in autoimmune diseases.
This role sits at the intersection of LLM-driven in silico modeling, structural biology, and translational cell therapy development. The successful candidate will design and optimize highly selective binders and oversee their integration into engineered cell therapy platforms.
Mission
Build and operate a proprietary platform for de novo design of binders targeting pathogenic T cell receptors and translate them into functional CAR constructs through integrated computational and wet-lab workflows.
Key ResponsibilitiesML-Driven Binder Design, Binder Optimization & Specificity Engineering
* Develop computational binder design workflows (e.g., RFdiffusion, ProteinMPNN)
* Perform structural validation (e.g., AlphaFold, Boltz-2)
* Design cross-reactivity screening against TCR panels
* Lead and/or coordinate wet-lab validation and functional assays
* Establish iterative computational–experimental feedback loops
Protein Engineering
* Work with recombinant antibody engineering platforms (VHH, scFv, or IgG formats)
* Understand purification workflows and basic biophysical characterization
* Translate sequence-level design decisions into experimentally robust constructs
Display Technologies
* Work with yeast or phage display platforms
* Design focused and diversified libraries (e.g., CDR mutagenesis strategies)
* Develop positive and counter-selection strategies
* Interpret enrichment data and sequencing outputs
* Identify and correct selection biases (e.g., framework-driven enrichment)
Ideal Profile
* PhD in computational biology, structural biology, immunology, or related field
* Demonstrated ability to bridge computation and wet lab
* Experience in CAR-T or TCR biology is strongly preferred
Computational Skill Set
* Advanced Python and PyTorch programming skills
* Experience with RFdiffusion and ProteinMPNN
* Experience with AlphaFold-based complex prediction
* Experience with Boltz-2 or similar structural prediction tools
* HPC/GPU workflow management
* Experience with structural analysis tools (PyMOL, ChimeraX)
Why Join Match Medicines
* Work on a first-in-class approach to selectively target pathogenic T cells
* Build and own a cutting-edge AI-driven protein design platform
* Directly translate computational designs into therapeutic cell products
* Operate at the interface of immunology, AI, and cell therapy
* Join a highly experienced, mission-driven team in Munich