Principal Machine Learning Scientist
- Develop, evaluate, and apply machine learning algorithms and workflows for accelerating early-stage drug discovery, including but not limited to (i) de-novo design of biomolecules, (ii) assessment of target druggability across therapeutic modalities (iii) design of drug delivery systems, (iv) identification of novel druggable pockets and epitopes, (vi) characterization of protein-protein and protein-ligand interactions;
- Contribute to the implementation, validation, and improvement of machine learning tools and software solutions that support drug discovery activities;
- Identify opportunities for accelerating ongoing drug discovery projects with internal and external AI capabilities;
- Communicate, educate, and engage with a broad set of stakeholders (chemists, biologists, computational/data scientists, R&D leadership) on the state of technology and the progress of key internal initiatives. Engage with the broader scientific community through publications, talks, and open-source;
- Keep up to date with the latest advances in AI-driven modeling of biomolecular structure and dynamics.
- Ph.D. degree in Computational Chemistry/Biology, Chem/Bioinformatics, Chemical/Biological/Molecular Engineering, or a related field at the intersection of life sciences and computer science;
- Deep expertise with state-of-the-art machine learning methods for modeling biomolecules, like co-folding and/or generative methods for protein design;
- Expertise in handling, processing, integrating and analyzing large datasets related to drug development research, including biochemical, biophysical, and structural biology data;
- Strong programming skills in Python;
- Demonstrated commitment to scientific rigor, a track record of scientific excellence, strong analytical thinking, and a high degree of self-motivation;
- Excellent written and verbal communication.
- 5+ years of relevant post-PhD experience, including 2+ years in industry;
- Experience with established, physics-based protein modelling methods like Molecular Dynamics and/or Rosetta;
- Experience in coordinating small, interdisciplinary teams and ability to articulate their impact to managerial stakeholders;
- Strong record of publications or patents related to machine learning solutions for biomolecular modeling.
YOUR APPLICATION
Bayer offers a wide variety of competitive compensation and benefits programs. If you meet the requirements of this unique opportunity, and want to impact our mission Health for all, Hunger for none, we encourage you to apply now. Be part of something bigger. Be you. Be Bayer.
To all recruitment agencies: Bayer does not accept unsolicited third party resumes.
Bayer is an Equal Opportunity Employer/Disabled/Veterans
Bayer is committed to providing access and reasonable accommodations in its application process for individuals with disabilities and encourages applicants with disabilities to request any needed accommodation(s) using the contact information below.
Equal Opportunity Employer Statement: Notice for U.S. Visitors: All information on this site is subject to compliance with local rule and regulations as they may vary from time to time and across different geographies, including, without limitation, U.S. Executive Orders. Bayer is an E-Verify Employer. Location: United States : Massachusetts : Cambridge Division: Pharmaceuticals Reference Code: 865491 Contact Us Email: [email protected]
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