Bristol-Myers Squibb - San Diego, CA

posted 3 months ago

Full-time - Mid Level
Hybrid - San Diego, CA
Chemical Manufacturing

About the position

The Cheminformatics team at Bristol Myers Squibb is seeking an exceptional scientist with a strong interest in leveraging artificial intelligence and machine learning for molecular design. This role is pivotal in utilizing cutting-edge techniques to accelerate the drug discovery process, from hit identification through candidate nomination, and involves active participation in therapeutic projects. The successful candidate will possess a broad knowledge of modern data science methods, particularly in machine learning, to advance multi-objective molecular design efforts. Expertise in generative molecular design, particularly as it applies to therapeutic projects, is highly desirable. The candidate must also have a solid understanding of chemistry and the ability to effectively communicate with collaborative scientists from diverse backgrounds. Key objectives for this position include identifying and employing machine learning methods to optimize chemical structures within the context of therapeutic projects, as well as enabling other scientists within the team to leverage these tools and methods in their own projects. The selected candidate will join a research team known for its impactful contributions across various modalities and therapeutic areas. This is an exciting opportunity to combine physics-based modeling with data analytics and machine learning to accelerate drug discovery and ultimately benefit patients in need. The work environment at Bristol Myers Squibb is characterized by a commitment to diversity and collaboration, where employees are encouraged to grow and thrive through unique opportunities. The company recognizes the importance of work-life balance and offers a variety of competitive benefits and programs to support employees in achieving their personal and professional goals. The Cheminformatics team is dedicated to fostering an inclusive culture that promotes innovation and accountability, ensuring that every employee plays a vital role in transforming patients' lives through science.

Responsibilities

  • Utilize artificial intelligence and machine learning techniques to accelerate the drug discovery process.
  • Participate directly in therapeutic projects from hit identification through candidate nomination.
  • Identify and implement machine learning methods for chemical structure optimization.
  • Collaborate with scientists from various disciplines to enhance project outcomes.
  • Develop and apply suitable machine learning algorithms to produce meaningful predictive models.
  • Contribute to the advancement of multi-objective molecular design efforts.
  • Communicate effectively with team members and stakeholders regarding project progress and methodologies.

Requirements

  • Bachelor's Degree with 5+ years of academic/industry experience, or a Master's Degree with 3+ years of experience, or a Ph.D. with no experience required.
  • Broad knowledge of modern data science methods, particularly in machine learning.
  • Expertise in generative molecular design with applications to therapeutic projects.
  • Proficiency in programming and scripting languages such as Python, C/C++, and/or R.
  • Experience with machine learning and cheminformatics libraries such as TensorFlow, Keras, PyTorch, Pandas, Scikit-Learn, DeepChem, RDKit, or OEchem.
  • Ability to critically assess experimental data and incorporate data knowledge into model development.
  • Strong communication skills and a collaborative mindset.

Nice-to-haves

  • Ph.D. with 0-2+ years of relevant experience in Artificial Intelligence or Machine Learning applications to molecular design.
  • Postdoctoral or industry experience in related fields.
  • Experience in cheminformatics, computational chemistry, and/or molecular modeling.

Benefits

  • Medical, pharmacy, dental, and vision care.
  • Wellbeing support programs such as the BMS Living Life Better program and employee assistance programs (EAP).
  • Financial well-being resources including a 401(K).
  • Short- and long-term disability insurance, life insurance, and supplemental health insurance.
  • Paid national holidays and optional holidays, Global Shutdown days between Christmas and New Year's holiday.
  • Up to 120 hours of paid vacation and up to two paid days to volunteer.
  • Sick time off and summer hours flexibility.
  • Parental, caregiver, bereavement, and military leave.
  • Family care services including adoption and surrogacy reimbursement, fertility/infertility benefits, and support for traveling mothers.
  • Tuition reimbursement and a recognition program.
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