Associate Director - Molecular Informatics
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.
We seek a collaborative and highly innovative computational research leader to join our Predictive Sciences team and develop novel approaches at the interface of structural bioinformatics, chemoinformatics, and predictive molecular design that originate, elucidate, and prioritize the next generation of targeted protein degradation therapies for both hematological and solid tumor indications.
Working alongside BMS Research & Early Development colleagues in the Protein Homeostasis Center of Excellence, Small Molecule Drug Design and other teams in the global Informatics and Predictive Sciences (IPS) department, the successful applicant will play a key scientific role in shaping the future of our most advanced protein degrader compound libraries to pursue therapeutic opportunities in spaces beyond the reach of conventional small molecule drug approaches.
This role offers the opportunity to directly impact the origination and delivery of transformational therapies in key diseases of unmet medical need by innovating and applying leading computational research approaches. A strong track record in the inter-disciplinary application of computational research at the junction of biology and chemistry to empower complex life sciences and therapeutic discovery objectives is imperative.
- Build and lead an internal team of structural bioinformatics, chemoproteomics, chemogenomics and systems biology researchers.
- Drive predictive research across multi-dimensional compound profiling datasets to elucidate functional activity phenotypes and their association with molecular structure
- Collaborate closely with Computer Aided Drug Design team to leverage findings within predictive structure-property relationship models for chemical optimization and compound library expansion into novel chemical space.
- Pioneer drug-target interaction modeling via application of state-of-the-art methods for protein folding and partner with Protein Homeostasis colleagues to leverage predicted protein structures for identification and refinement of neosubstrate recruitment modes.
- Design and implement computational strategies that elucidate protein degradation biophysics, kinetics and substrate specificity.
- Collaborate in matrix teams to prioritize protein degradation MoAs and predict potential therapeutic effects on patient disease states in key indications.
- 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. in interdisciplinary fields including computer science, systems biology, structural bioinformatics, chemoinformatics from a recognized higher-education establishment.
- 10+ years of research experience in applying predictive computational approaches to elucidate complex interactions between human disease biology and therapeutic drug modalities in university, pharma, or biotech research environments.
- Demonstrated ability to integrate heterogeneous data sources and apply predictive, multivariate research approaches to integrated molecular and chemistry datasets.
- Proven expertise in development and implementation of algorithms to distill, analyze and interpret complex drug MoA and/or molecular perturbation datasets.
- Experience of computational biology research on a wide variety of molecular and phenotypic profiling platforms, including proteomics, mRNA profiling and high content imaging assays.
- Strong working knowledge of molecular properties, chemical interactions, and drug discovery plus experience with contemporary cheminformatics methods and related research tools (e.g., RDKit).
- Expertise in state-of-the-art machine learning methods, such as graph convolutional neural networks, generative models, and reinforcement learning.
- Track record of peer-reviewed publications in top-tier scientific journals and supervision of computational research.
- Proven problem-solving skills, collaborative nature, and adaptability across disciplines.
- Excellent verbal and written communication skills. Fluent verbal and written English language skills prerequisite.
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.
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