Scientist Machine learning - Biomolecular Interactions

at  BristolMyers Squibb

WORKING WITH US

Challenging. 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.
We seek a collaborative and highly innovative computational scientist to join our Predictive Sciences team and develop predictive models using cutting-edge machine learning/artificial intelligence techniques to discover novel therapeutic opportunities.
This position will work alongside colleagues in Informatics & Predictive Sciences (IPS), Protein Homeostasis, Small Molecule Drug Design and other teams in BMS Research, and play a key scientific role in shaping the future of our most advanced therapeutic approaches, primarily focusing on protein degradation, to pursue opportunities beyond the reach of conventional small molecules. We welcome applications from candidates who are passionate about learning new drug discovery paradigms, bringing new medicines to the patients, and comfortable working in a fast-paced and highly collaborative environment.

BASIC REQUIREMENTS:

Bachelor’s Degree and 5 + years of Academic / Industry experience
or
Master’s Degree and 3+ years of Academic / Industry experience
or
PhD in computer science, bioinformatics, machine learning or computational biology

PREFERRED QUALIFICATIONS:

• Ph.D. in machine learning with 2+ years of post-doctoral experience in applying computational and analytical approaches in university, pharma, or biotech settings.
• Expertise in developing state-of-the-art deep learning techniques, including diffusion models and large language models.
• Experience with deep learning frameworks such as PyTorch, TensorFlow, Keras, including underlying implementations.
• Demonstrated ability to design & engineer multiple molecular representations and apply predictive, multivariate research approaches to integrated molecular and chemistry datasets.
• Strong working knowledge of protein structure/folding and protein-ligand interaction prediction.
• Strong problem-solving skills and ability to work independently and as part of a team.
• Excellent communication and interpersonal skills.
  If you come across a role that intrigues you but doesn’t perfectly line up with your resume, we encourage you to apply anyway. You could be one step away from work that will transform your life and career.

• Interrogate properties of protein-protein and protein-ligand interaction surfaces and their molecular representations.
• Develop and apply state-of-the-art artificial intelligence/machine learning algorithms, including geometric deep learning and graph-based models, to predict complex biomolecular interactions and their selectivity.
• Devise AI/ML strategy to predict, or de novo design, small molecule ligands that enhance complex protein-protein interaction interfaces.
• Design experiments to elucidate protein interactions at the molecular level, process and analyze data for model training or to validate findings.
• Communicate results and findings to scientific project teams and stakeholders.
• Contribute to planning and execution of collaborative projects with leading academic and commercial research groups worldwide.