Principal Scientist, Machine Learning (Protein Design)
Skills
- Strong foundation in machine learning and deep learning techniques.
- Expertise in sequence- and structure-based protein and antibody design.
- Proficiency with protein design tools such as AlphaFold, ESM, ProteinMPNN, RF-Diffusion, Rosetta.
- Advanced skills in Python programming and ML frameworks like PyTorch, TensorFlow, JAX.
- Capability to develop novel AI and biomolecular design methods.
Responsibilities
- Design and conduct independent machine learning research focused on antibody binder design.
- Develop robust, production-quality models advancing antibody engineering and de novo design.
- Collaborate closely with experimental teams to integrate computational and bench capabilities.
- Communicate scientific insights effectively to leadership and cross-functional teams.
- Manage and mentor the Machine Learning team contributing to the AND-Body platform.
- Foster a collaborative, high-performing, and accountable team culture.
- Drive alignment and collaboration with key stakeholders to ensure business success.
Education
- PhD in biochemistry, biophysics, computational chemistry, computational biology, computer science, machine learning, or related computational disciplines applied to biological or chemical problems.
Benefits
- Opportunity to work at a dynamic, innovative biotech company on cutting-edge antibody design.
- Collaborative and entrepreneurial work environment.
- Mentorship and clear career development pathways.
- Being part of a team shaping next-generation biotherapeutics.
Average salary estimate
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