Senior Principle Scientist - Machine Learning – Predictive Drug Substance Research
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 are looking for experienced Machine Learning Scientists who will be members of a Informatics & Predictive Sciences multi-disciplinary team working in a fast-paced research environment. 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). You will be responsible for research and development of novel AI/ML methods and workflows that help to accelerate discovery of novel pharmaceuticals and establishing new chemical-pathology-pharmaceutical target relationships. In collaboration with domain experts, academic and industrial partners, you will have the opportunity to solve real problems on big data.
Are you a self-motivated learner and enjoy solving problems? Do you want to help build something at the intersection of chemical/biological sciences and machine learning that’s transformational? Join us and help revolutionize the application of machine-learning for patient benefit!
- Join internal project teams to advance protein structure and ligand-based discovery.
- Pioneer the science of drug-target interaction modeling and apply via application of state-of-the-art methods for protein folding.
- Create and improve novel computational methods to support multivariate, multi-task neural networks in chemo-centric mechanism-of-actions identification, off-target risk assessment, and optimization strategies.
- Create and improve novel molecular descriptors integrating proprietary BMS data
- Develop high-dimensional machine-learning-based methods based on multi-modal datasets to enable project advancement.
- Communicating results with internal and external project teams.
Qualifications and Experience:
• Ph.D. or equivalent in Computer science, Mathematics, Statistics or a related field
• Knowledge of state-of-the-art machine learning methods.
• In-depth understanding of deep learning algorithms such as Graph Convolutional Networks, Transformer architecture, Generative Models.
• Experience with one or more of deep graph learning (e.g., graph convolutional networks, neural message passing networks) and generative models (e.g., VAE, GAN, Flow).
• Experience with Monte-Carlo tree search, genetic algorithms, and reinforcement learning.
• Proficiency with deep learning frameworks (PyTorch is preferable, JAX, TensorFlow).
• Experience with probabilistic models is a plus (e.g., Gaussian Processes, Bayesian Neural Networks).
• Publication record in machine learning, ideally publications in top machine learning conferences such as NeurIPS, ICML, ICLR, or AISTATS.
• Basic knowledge of molecular properties and/or chemical reactions is a plus.
• Experience with cheminformatics and related libraries (e.g., RDKit) is a plus.
• Excellent oral and written communication, presentation, and analytical skills.
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 email@example.com. Visit careers.bms.com/eeo-accessibility to access our complete Equal Employment Opportunity statement.