Scientist, Cheminformatics - Machine Learning & Artificial Intelligence

Bristol-Myers Squibb - Princeton, NJ

Full-time - Mid Level

Princeton, NJ

Chemical Manufacturing

About the position

The Cheminformatics team at Bristol Myers Squibb is seeking an exceptional scientist with a strong interest in leveraging artificial intelligence and machine learning for molecular design. This role is pivotal in accelerating the drug discovery process, from hit identification through candidate nomination, and involves active participation in therapeutic projects. The successful candidate will utilize cutting-edge techniques to enhance multi-objective molecular design efforts, focusing on generative molecular design applicable to therapeutic projects. A broad knowledge of modern data science methods, particularly in machine learning, is essential to drive chemical structure optimization within the context of these projects. The candidate will also be responsible for enabling other scientists within the team to benefit from these tools and methods, fostering a collaborative environment that enhances the overall research output. The selected scientist will join a research team known for its impactful contributions across various modalities and therapeutic areas. This position offers an exciting opportunity to combine physics-based modeling with data analytics and machine learning, ultimately accelerating drug discovery and delivering significant benefits to patients. The role requires effective communication with collaborative scientists from diverse backgrounds, ensuring that the integration of cheminformatics, computational chemistry, and machine learning is seamless and productive. The ideal candidate will possess a strong work ethic, creativity, and a problem-solving mindset, along with excellent communication skills to articulate complex concepts clearly and effectively. A track record of publications in peer-reviewed scientific journals will be a significant advantage, showcasing the candidate's expertise and contributions to the field.

Responsibilities

• Utilize artificial intelligence and machine learning techniques to accelerate the drug discovery process.
• Participate directly in therapeutic projects, contributing to hit identification and candidate nomination.
• Drive multi-objective molecular design efforts using modern data science methods, particularly machine learning.
• Identify and implement machine learning methods for chemical structure optimization.
• Enable team members to leverage machine learning tools and methods in their projects.
• Collaborate with scientists from various disciplines to enhance the drug discovery pipeline.
• Contribute to the development of predictive models based on experimental data and diverse data sets.

Requirements

• Bachelor's Degree with 5+ years of academic/industry experience, or a Master's Degree with 3+ years of experience, or a Ph.D. in Chemistry or Computational Chemistry.
• Broad knowledge of modern data science methods with an emphasis on machine learning.
• Expertise in generative molecular design with applications to therapeutic projects.
• Experience in machine learning or artificial intelligence, particularly in cheminformatics or computational chemistry.
• Proficiency in programming and scripting languages such as Python, C/C++, and/or R.
• Familiarity with machine learning and cheminformatics libraries such as TensorFlow, Keras, PyTorch, Pandas, Scikit-Learn, DeepChem, RDKit, or OEchem.
• Ability to critically assess experimental data and incorporate data knowledge into the development of machine learning algorithms.
• Willingness to collaborate across functional teams in a multidisciplinary environment.
• Strong communication skills and a track record of publications in peer-reviewed scientific journals.

Nice-to-haves

• Ph.D. with 0-2+ years of relevant experience focusing on AI or ML applications in molecular design.
• Postdoctoral or industry experience in related fields.
• Experience with cheminformatics, computational chemistry, and/or molecular modeling.

Benefits

• Competitive salary and benefits package.
• Opportunities for professional development and career growth.
• Flexible work environment with a focus on work-life balance.
• Diversity and inclusion initiatives within the workplace.