|
Scientist, Machine Learning, Active Learning and Discovery - Cambridge Massachusetts
Company: Disability Solutions Location: Cambridge, Massachusetts
Posted On: 05/03/2024
Working 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. Read more: careers.bms.com/working-with-us .Scientist, Machine Learning, Active Learning and DiscoveryBMS encompasses a broad range of disciplines to enable a robust pipeline of drug candidates aimed at serious diseases. Chemistry is a core capability in Small Molecule & Drug Discovery with innovative scientists working in medicinal chemistry, radiochemistry, analytical chemistry, and large-scale synthesis. Within SMDD our Lead Discovery and Optimization (LDO) team is responsible for high throughput screening, compound storage and distribution, primary assays to support discovery programs, and compound profiling to explore drug liabilities in vitro. LDO scientists discover and adopt cutting edge assay technologies that utilize state-of-the-art automation to drive speed and efficiency. Our Molecular Structure and Design team embraces novel approaches to computer-aided drug design, machine learning, and structural biology. The integration of these disciplines provides a seamless and highly interactive environment for discovery scientists to learn, develop, and innovate. Working in partnership with our disease area experts in the Thematic Research Centers provides an exciting pathway to discover and deliver medicines to patients in need.We seek an enthusiastic and collaborative machine learning scientist with a focus on AI/ML methods to join our Small Molecule Drug Discovery team. In this role, you will contribute to a thoughtful, exciting, and cross-functional group applying AI to drive the development of groundbreaking therapies across multiple modalities, including targeted protein degraders. This role focuses on developing cutting-edge techniques to analyze and interpret machine learning models to originate novel therapeutics for our pipeline.You will work as a valued member on a multidisciplinary team that is committed to leveraging predictive methods to optimize synthesis and screening of promising drug candidates. This 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 seek diverse perspectives as we pursue scientific innovation, and we expect all candidates to participate in maintaining our respectful and inclusive team. We encourage inquiries from those with a strong background in AI/ML who also have a keen interest in interdisciplinary application of computational approaches to life sciences data.Responsibilities: - Develop and apply deep learning methods to assess model trustworthiness and data fairness by employing techniques such as uncertainty quantification and explainable ML
- Establish workflows to accelerate hit discovery through active learning-guided synthesis and screening
- Integrate and implement approaches that enable closed-loop discovery cycles in collaboration with biologists, chemists, and modelers
- Contribute to the principled exploration of novel therapeutic modalities and their application to research portfolio
- Effectively communicate methods, results, and recommendations in multiple settings such as team and project meetings, seminars, academic conference, and journal publications
- Educate and mentor scientists across the organization on AI/ML methods Basic Qualifications: Bachelor's Degree with 5+ years of academia / industry experienceOrMaster's Degree with 3+ years of academia / industry experienceOrPh.D. and no years of experience Preferred Qualifications:
- Ph.D. in computer science, cheminformatics, bioinformatics, or a related field
- Strong experience with modern deep learning methods; preferably with demonstrated application of models in the areas of active learning and explainable ML
- Expertise in scientific programming languages (e.g., Python, R) and machine learning libraries (e.g., PyTorch, Tensorflow)
|
|