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Senior Scientist, Machine Learning, Molecular Discovery - San Diego California
Company: Web-atrio Location: San Diego, California
Posted On: 11/07/2024
Senior Scientist, Machine Learning, Molecular DiscoveryStatus: ArchivedCompany: Bristol Myers SquibbLocation:Expiration: 2023-08-01How to Apply: Job DescriptionWorking with UsChallenging. Meaningful. Life-changing. Those aren't words that are usually associated with a job. But working at Bristol Myers Squibb is anything but usual. Here, uniquely interesting work happens every day, in every department. From optimizing a production line to the latest breakthroughs in cell therapy, this is work that transforms the lives of patients, and the careers of those who do it. You'll get the chance to grow and thrive through opportunities uncommon in scale and scope, alongside high-achieving teams rich in diversity. Take your career farther than you thought possible.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.OverviewWe seek an enthusiastic and team-oriented 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, small-molecule therapies.You will be a valued member on a cross-functional team that seeks to continuously improve the process by which novel compounds are rationally designed and experimentally evaluated. The successful candidate will perform key research activities, including: - Developing and implementing machine learning models to predict attributes of therapeutic compounds.
- Leveraging active machine learning approaches to guide experimental discovery activities focused on exploring vast chemical space.
- Driving in silico design of novel molecular therapies through generative modeling approaches.This individual will work as part of a multidisciplinary team that is focused primarily 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 the discovery and development of new therapies.Responsibilities
- Build and apply advanced deep learning models to predict molecular attributes that govern protein degradation, cellular phenotype, and disease state (e.g., using self-supervised learning, large language models, geometric deep learning, or graph neural networks).
- Leverage AI/ML approaches to guide experimental study design and to steer chemical design efforts towards small molecules with high therapeutic value (e.g., using generative active learning, reinforcement learning, autonomous discovery).
- 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 validate in silico findings and improve ML workflows.
- 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.Basic Qualifications
- Bachelor's Degree with machine learning focus in computer science, bioinformatics, computational chemistry, or a related field from a recognized higher-education institution and 7+ years of academic / industry experience.
- OR Master's Degree with machine learning focus in computer science, bioinformatics, computational chemistry, or a related field from a recognized higher-education institution and 5+ years of academic / industry experience.
- OR PhD with machine learning focus in computer science, bioinformatics, computational chemistry, or a related field from a recognized higher-education institution and 2+ years of academic / industry experience.Preferred Qualifications
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