Senior Principal Scientist

2 weeks ago


Redwood City, California, United States Bristol-Myers Squibb Full time
Job Description

Bristol-Myers Squibb is seeking a highly skilled Senior Principal Scientist to join our team in the Informatics and Predictive Sciences (IPS) department. As a key member of our team, you will be responsible for pioneering machine learning research into antibody-antigen interaction modeling and design using internal and external datasets.

Responsibilities:
  • Pioneer machine learning research into antibody-antigen interaction modeling and design using internal and external datasets.
  • Partner with project teams to advance sequence- and structure-based antibody discovery and design.
  • Develop and implement computational approaches and prediction algorithms that can map linear and three-dimensional epitopes, optimize binding scaffolds and library design to guide screening, predict and mature the affinity of antibody hits, and assess potential liabilities and optimal development options.
  • Communicate findings and recommend follow-up actions in multiple settings such as 1:1, seminars, group, and project meetings.
Requirements:
  • Bachelor's Degree in structural bioinformatics, computational biology, computer science, engineering, physics, or a similar program and 10+ years of academic / industry experience.
  • Master's Degree in structural bioinformatics, computational biology, computer science, engineering, physics, or a similar program and 8+ years of relevant experience.
  • PhD in structural bioinformatics, computational biology, computer science, engineering, physics, or a similar program and 6+ years of academic / industry experience.
Preferred Qualifications:
  • Ph.D in structural bioinformatics, computational biology, computer science, engineering, physics, or a similar program with 6+ years of relevant experience.
  • Deep expertise in modern neural network architectures including transformers, autoencoders, CNNs, equivariant GNNs, and diffusion models.
  • Familiarity with PyTorch and its ecosystem, as well as other platforms such as scikit-learn, and design of effective experiments and metrics.
  • Experience with deep learning structure prediction programs like AlphaFold2, physics-based modelling and protein docking packages like Rosetta, and state-of-the-art machine learning approaches for protein sequence data.
What We Offer:
  • A competitive salary range of $159,000 to $185,000, plus incentive cash and stock opportunities (based on eligibility).
  • A comprehensive benefits package, including medical, pharmacy, dental and vision care, wellbeing support, financial well-being resources, and more.


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