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Job Details


Bristol Myers Squibb

Scientist, Generative Machine Learning, Predictive Sciences

Science and Research

Scientist

No

San Diego, California, United States

At Bristol Myers Squibb, we are inspired by a single vision – transforming patients’ lives through science. In oncology, hematology, immunology and cardiovascular disease – and one of the most diverse and promising pipelines in the industry – each of our passionate colleagues contribute to innovations that drive meaningful change. We bring a human touch to every treatment we pioneer. Join us and make a difference.

Overview

We seek an enthusiastic and collaborative machine learning scientist to join our Predictive Sciences team. This individual will contribute to our growing effort to apply cutting-edge AI/ML techniques toward the development of novel therapies to treat cancer and hematological malignancies.

The successful candidate will pursue key research objectives, including development and implementation of generative machine learning models for in silico small-molecule drug design, and prediction of therapeutic potential based on features learned from diverse high-throughput screening data.

This individual will work as part of a multidisciplinary team that is focused on targeted protein degradation as a therapeutic modality. You will be able to perform pioneering and impactful research alongside computational scientists, experimental biologists and chemists, as we work towards rational design of novel compounds.

The role offers unprecedented opportunity to impact directly the origination and delivery of transformational and life-changing therapies in key diseases of unmet medical need. We encourage inquiries from those with a strong background in AI/ML who also have a strong interest in innovation and interdisciplinary application of computational approaches to life sciences data.

Responsibilities

  • Build and apply advanced deep learning models to drive the design of small-molecule compounds (e.g., using graph-based models or self-supervised learning approaches)
  • Leverage AI/ML approaches to produce interpretable insights regarding key drug features that govern effects on protein degradation, cellular phenotype, and disease states.
  • Analyze chemistry, proteomics, transcriptomics, and other high throughput assay data from internal, public, and partner sources.
  • Collaborate as a member of cross-functional teams to design experiments, guide data generation, and validate in silico findings.
  • Author scientific reports, and present methods, results, and conclusions to publishable standard.
  • Contribute to planning and execution of collaborative projects with leading academic and commercial research groups worldwide.

Background experience & complementary knowledge

  • Ph.D. with machine learning focus in computer science, bioinformatics, computational chemistry, or a related field from a recognized higher-education institution
  • Strong experience in applying contemporary deep learning methods, preferably with demonstrated application of either generative, graph-based, or geometric deep learning approaches
  • Expertise in scientific programming languages (e.g., Python, R) and libraries (e.g., PyTorch, Tensorflow), cloud-based computing, and data manipulation.
  • Demonstrated problem-solving skills, adaptability across disciplines, and collaborative nature.
  • Excellent verbal and written communication skills. Verbal and written English language fluency are prerequisite.
  • Familiarity with public chemical databases and molecular profiling datasets is a plus.
  • Prior research projects in pharma/biotech, university, or hospital environments are a plus.

Around the world, we are passionate about making an impact on the lives of patients with serious diseases. Empowered to apply our individual talents and diverse perspectives in an inclusive culture, our shared values of passion, innovation, urgency, accountability, inclusion and integrity bring out the highest potential of each of our colleagues.

Bristol Myers Squibb recognizes the importance of balance and flexibility in our work environment. We offer a wide variety of competitive benefits, services and programs that provide our employees with the resources to pursue their goals, both at work and in their personal lives.

Physical presence at the BMS worksite or physical presence in the field is an essential job function of this role which the Company deems critical to collaboration, innovation, productivity, employee well-being and engagement, and enhances the Company culture.

To protect the safety of our workforce, customers, patients and communities, the policy of the Company requires all employees and workers in the U.S. and Puerto Rico to be fully vaccinated against COVID-19, unless they have received an exception based on an approved request for a medical or religious reasonable accommodation. Therefore, all BMS applicants seeking a role located in the U.S. and Puerto Rico must confirm that they have already received or are willing to receive the full COVID-19 vaccination by their start date as a qualification of the role and condition of employment. This requirement is subject to state and local law restrictions and may not be applicable to employees working in certain jurisdictions such as Montana. This requirement is also subject to discussions with collective bargaining representatives in the U.S.

Our company is committed to ensuring that people with disabilities can excel through a transparent recruitment process, reasonable workplace adjustments and ongoing support in their roles. Applicants can request an approval of accommodation prior to accepting a job offer. If you require reasonable accommodation in completing this application or if you are applying to a role based in the U.S. or Puerto Rico and you believe that you are unable to receive a COVID-19 vaccine due to a medical condition or sincerely held religious belief, during or any part of the recruitment process, please direct your inquiries to adastaffingsupport@bms.com. Visit careers.bms.com/eeo-accessibility to access our complete Equal Employment Opportunity statement.

Any data processed in connection with role applications will be treated in accordance with applicable data privacy policies and regulations.