Principal Machine Learning Scientist

Stack

Responsibilities

• ▹Lead the development, evaluation, and application of ML algorithms and workflows for biomolecule characterization and de novo design
• ▹Identify opportunities to accelerate ongoing drug discovery projects through internal and external AI capabilities
• ▹Communicate and collaborate with chemists, biologists, computer and data scientists, R&D leadership, and consortium partners
• ▹Track the latest advances in computational modeling of biomolecular structures, interactions, and functions

Requirements

• ▹PhD in computational chemistry/biology, chem-/bioinformatics, or a related field bridging life sciences and computer science
• ▹Several years of post-PhD professional experience, ideally including industry exposure
• ▹Strong knowledge of modern ML methods for biomolecule modeling (sequence-to-function models, protein language models, co-folding, inverse folding, controllable generative methods)
• ▹Experience with ML-based workflows for characterizing biomolecular interactions, drugability assessment, candidate screening, and therapeutic/delivery system design
• ▹Experience processing, integrating, and analyzing large drug discovery datasets (sequence, omics, biochemical, biophysical, structural biology)
• ▹Strong Python skills (PyTorch, Pandas, scikit-learn) and experience with collaborative software development best practices

Nice to have

• ▹Familiarity with modern bioinformatics tools (e.g. MMseqs, Foldseek)

Soft skills

What we offer

• ▹Annual gross salary of €104,300–126,500 (full-time) plus a variable component
• ▹Hybrid work models and part-time options
• ▹Company daycare, childcare support, and family care leave
• ▹Access to the Bayer Learning Academy, coaching, and mentoring programs
• ▹Free health checks and health seminars

About the company

Bayer is a global pharmaceutical and life science company working to address the world's food and healthcare challenges.