Head of Machine Learning Research

Role: Head of Machine Learning Research responsible for advancing ML-enabled molecular design within Bayer’s drug discovery pipeline. Objectives include defining the strategic ML roadmap, developing predictive and generative models, and integrating them into discovery projects to accelerate candidate nomination. Responsibilities encompass setting technical standards, collaborating with multidisciplinary teams (medicinal chemistry, structural biology, DMPK, safety), and overseeing platform development for property prediction, structure-based ML, and synthesis planning. The role involves building and leading a ~25-person team, managing budgets, external collaborations, and representing ML capabilities to R&D leadership. Qualifications: PhD in computational chemistry, structural biology, or related, with expertise in modern ML methods (deep learning, transformers, Bayesian optimization), and a proven track record impacting real drug programs. Preferred: 12+ years’ experience, previous leadership in pharma or biotech, experience with modalities beyond small molecules (PROTACs, peptides, oligonucleotides), and external scientific recognition. High-value specifics include biologics/biophysical data, AI/machine learning platform strategies, and application across early to late-stage drug discovery. Work setup: locations in Cambridge, MA, or Whippany, NJ, with significant cross-disciplinary engagement and strategic leadership responsibilities.