Scientist, Predictive Biology and AI - Princeton NJ
VetJobs, Princeton, NJ, United States
Overview
The Predictive Biology and AI (PBAI) team within BMS Research develops and applies cutting-edge methods to address patient needs and answer fundamental questions in Oncology, Neuroscience, and other application areas. We work closely with our wet-lab partners to both test and deliver our predictions into the pipeline as well as integrate the data they generate into our models. The successful candidate will thoughtfully evaluate and adapt state-of-the-art AI models and techniques to challenges in cell engineering and target discovery. The role offers the opportunity to impact directly the delivery of truly transformational and life-changing therapies in key diseases of unmet medical need.
Responsibilities
Apply, adapt, and in some cases create multi-modal foundation models such as large language models (LLMs), diffusion models, and encoder architectures to answer biological domain-specific questions
Address real-world biological modeling challenges such as data sparsity, class imbalance, noise, experimental bias, and heterogeneity of effects
Thoughtful model evaluation that incorporates appropriate benchmarks, statistical tests, and problem understanding to support technical and business decisions
Work in close collaboration with partners across the organization including wet-lab scientists, Research IT, and other computational scientists to broaden the impact of AI developments
Maintain and share up-to-date knowledge of modern advances in the field, including presenting work at public conferences
Auto req ID
469795BR
Minimum Education Required
Bachelors
Job_Category
Management
Additional Qualifications/Responsibilities
Basic Qualifications
Bachelor's Degree 5+ years of academic / industry experience
Or Master's Degree 3+ years of academic / industry experience
Preferred Qualifications
Or PhD No experience required
A Ph.D. with 0+ years industry research experience or an M.S. with 3+ years industry research experience in computer science, statistics, computational biology, or another quantitative field
Expert-level understanding of and experience using deep learning tools and approaches (transformer-based encoders/decoders, LLMs, reinforcement learning, etc.) as demonstrated through publications or projects
Hands-on experience leading the building and scaling of deep learning training pipelines on multi-GPU computational infrastructure using PyTorch, Huggingface, and/or other tools
Knowledge of or the ability to learn biological concepts and data types, including the ability to work and communicate effectively with biologists
Excellent verbal and written communication skills. Fluent verbal and written English language skills prerequisite
Experience building agentic workflows is a plus
Prior experience in pharmaceutical application areas is a plus
If you come across a role that intrigues you but doesnt 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.
Compensation Overview
Brisbane - CA - US: $141,150 - $171,042
Cambridge Crossing: $141,150 - $171,042
Princeton - NJ - US: $122,740 - $148,732
San Diego - CA - US: $135,010 - $163,605
Seattle - WA: $135,010 - $163,605
Location
Princeton, New Jersey
Job Code
Pharmaceutical
Affiliate Sponsor
Bristol Myers Sqibb BMS
Salary Range
>$100,000
#J-18808-Ljbffr
The Predictive Biology and AI (PBAI) team within BMS Research develops and applies cutting-edge methods to address patient needs and answer fundamental questions in Oncology, Neuroscience, and other application areas. We work closely with our wet-lab partners to both test and deliver our predictions into the pipeline as well as integrate the data they generate into our models. The successful candidate will thoughtfully evaluate and adapt state-of-the-art AI models and techniques to challenges in cell engineering and target discovery. The role offers the opportunity to impact directly the delivery of truly transformational and life-changing therapies in key diseases of unmet medical need.
Responsibilities
Apply, adapt, and in some cases create multi-modal foundation models such as large language models (LLMs), diffusion models, and encoder architectures to answer biological domain-specific questions
Address real-world biological modeling challenges such as data sparsity, class imbalance, noise, experimental bias, and heterogeneity of effects
Thoughtful model evaluation that incorporates appropriate benchmarks, statistical tests, and problem understanding to support technical and business decisions
Work in close collaboration with partners across the organization including wet-lab scientists, Research IT, and other computational scientists to broaden the impact of AI developments
Maintain and share up-to-date knowledge of modern advances in the field, including presenting work at public conferences
Auto req ID
469795BR
Minimum Education Required
Bachelors
Job_Category
Management
Additional Qualifications/Responsibilities
Basic Qualifications
Bachelor's Degree 5+ years of academic / industry experience
Or Master's Degree 3+ years of academic / industry experience
Preferred Qualifications
Or PhD No experience required
A Ph.D. with 0+ years industry research experience or an M.S. with 3+ years industry research experience in computer science, statistics, computational biology, or another quantitative field
Expert-level understanding of and experience using deep learning tools and approaches (transformer-based encoders/decoders, LLMs, reinforcement learning, etc.) as demonstrated through publications or projects
Hands-on experience leading the building and scaling of deep learning training pipelines on multi-GPU computational infrastructure using PyTorch, Huggingface, and/or other tools
Knowledge of or the ability to learn biological concepts and data types, including the ability to work and communicate effectively with biologists
Excellent verbal and written communication skills. Fluent verbal and written English language skills prerequisite
Experience building agentic workflows is a plus
Prior experience in pharmaceutical application areas is a plus
If you come across a role that intrigues you but doesnt 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.
Compensation Overview
Brisbane - CA - US: $141,150 - $171,042
Cambridge Crossing: $141,150 - $171,042
Princeton - NJ - US: $122,740 - $148,732
San Diego - CA - US: $135,010 - $163,605
Seattle - WA: $135,010 - $163,605
Location
Princeton, New Jersey
Job Code
Pharmaceutical
Affiliate Sponsor
Bristol Myers Sqibb BMS
Salary Range
>$100,000
#J-18808-Ljbffr