August 2, 2021
Description
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.
In partnership with Discovery Science team members, you will be part of Informatics and Predictive Sciences at Bristol Myers Squibb and work at the nexus of physics-based simulation and machine-learning enabled methods. This role can be remote or located in any of our sites - New Jersey, Cambridge-MA, Seattle or California - (San Francisco, Redwood City, or San Diego). The role will focus on advancing the science of protein homeostasis-based therapeutics and focus on the development and application of in silico design methods to advance drugs with desirable pharmacological properties. You will be part of a group where computation is a central element in program advancement.
Are you a self-motivated learner and enjoy solving problems? Do you want to help build something transformational and revolutionary? Join us and help revolutionize the application of physics-based machine-learning for patient benefit!
Key responsibilities:
Use advanced biophysical simulation (e.g., atomistic, coarse-grained methods, FEP, replica-exchange) to advance protein degradation design.
Statistical modeling of high-dimensional, large-scale time series molecular simulation datasets.
Enhance our understanding of protein degradation biophysics, factors governing both degradation kinetics and protein substrate specificity.
Use enhanced molecular simulations and free energy calculations to characterize protein-protein association processes.
Develop new approaches for biasing molecular designs using machine-learning, collective variable discovery, and multiple endpoint optimization methods.
In close collaboration with project teams, apply a wide variety of drug-design and computational chemistry methods to improve potency, selectivity, and ADME properties while minimizing toxicological risk.
Enrich your expertise of contemporary computational chemistry methods via collaborations, both internal and external, and strong ongoing publication record on new methods.
Qualifications and Experience:
A completed Ph.D. in physical organic chemistry, computational chemistry or a related field with strong theoretical background as demonstrated by contributions to leading journals
A minimum of 6-10 years of relevant experience is preferred.
Experience in Markov-chain-based statistical sampling algorithms with sparse experimental data to guide iterative unbiased molecular simulations.
Expertise in enhanced sampling simulation science with particular emphasis on variational autoencoders and reinforcement learning approaches to guide reaction coordinate sampling.
Ability to represent computational chemistry on multiple drug discovery projects
A working knowledge of medicinal chemistry and drug discovery
Proven ability to collaborate with others.
Applicants are desired to have programming expertise in at least one programing language
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.
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 any part of the recruitment process direct your inquiries to adastaffingsupport@bms.com. Visit careers.bms.com/eeo-accessibility to access our complete Equal Employment Opportunity statement.
Contact
Contact Aditya Radhakrishnan (Aditya.Radhakrishnan@bms.com) with questions.