Senior Principal Investigator, Physical AI for Autonomous Discovery
About The Position
Johnson & Johnson Innovative Medicine is recruiting a Senior Principal Investigator for its In Silico Drug Discovery team. This hands-on scientific and technical individual-contributor role will develop Physical AI capabilities for autonomous laboratory experimentation, combining AI, robotics, laboratory automation, and scientific reasoning. The systems will perceive laboratory state, recommend actions, learn from experimental data, recover from errors, and improve experimental outcomes. The preferred location is Spring House, Pennsylvania, with consideration for candidates near Cambridge, Massachusetts. There is no remote option, and travel may be required as needed. The position reports to the Director, Physical AI for Autonomous Discovery. The role provides technical guidance and mentorship but does not include formal people-management responsibility. The position works closely with the Director and multidisciplinary teams across J&J IT and Data, Data Science & AI, automation, engineering, robotics, and scientific discovery.
Requirements
- PhD in artificial intelligence, machine learning, robotics, computer science, engineering, computational biology, or a related quantitative field, with substantial relevant research or industry experience.
- Demonstrated track record of independently developing and deploying AI systems in physical, scientific, or similarly complex environments.
- Deep expertise in multiple relevant areas, such as world models, reinforcement learning, Bayesian optimization, causal inference, multimodal AI, robotics, or scientific machine learning.
- Advanced software-development skills, including Python, modern machine-learning frameworks, experimental software design, testing, and reproducible deployment practices.
- Ability to define technical workstreams, solve ambiguous scientific problems, and deliver robust solutions with limited day-to-day direction.
- Strong communication, collaboration, and influence skills for working effectively across multidisciplinary teams in a matrix environment.
Nice To Haves
- Experience with self-driving laboratories, laboratory automation, or closed-loop scientific experimentation.
- Experience with vision-language-action models, digital twins, machine vision, robotic control, or multi-agent systems.
- Experience in biologics, drug discovery, life sciences, or another complex experimental domain.
- Experience deploying safety-critical or high-reliability AI systems with monitoring and governance controls.
Responsibilities
- Lead the hands-on design, development, and validation of AI models representing instruments, samples, reagents, robotic systems, workflows, and laboratory state.
- Develop and evaluate adaptive experimental optimization methods using active learning, Bayesian optimization, reinforcement learning, and multi-objective optimization.
- Implement physical error detection and correction, including anomaly recognition, root-cause assessment, workflow replanning, recovery actions, and appropriate human escalation.
- Build models that generate testable hypotheses for experimental failures, unexpected results, variability, and irreproducibility, and recommend discriminating follow-up experiments.
- Develop agentic and multi-agent capabilities for experiment planning and execution monitoring across Design-Make-Test-Analyze cycles.
- Translate scientific and operational needs into technical requirements, prototypes, and production-ready capabilities in partnership with automation, robotics, data science, engineering, and discovery scientists.
- Provide technical guidance, establish scientific best practices, and mentor colleagues without formal people-management responsibility.
- Embed calibrated uncertainty, safety constraints, monitoring, traceability, and governance into autonomous decision-making, escalating strategic tradeoffs to the Director as appropriate.
Benefits
- Annual performance bonus eligibility, subject to applicable plan terms and company discretion.
- Medical, dental, vision, life insurance, short- and long-term disability, business accident insurance, and group legal insurance.
- Eligibility to participate in the consolidated retirement plan (pension) and 401(k) savings plan.
- Vacation: up to 120 hours per calendar year.
- Sick time: up to 40 hours per calendar year.
- Holiday pay, including floating holidays: up to 13 days per calendar year.
- Work, Personal and Family Time: up to 40 hours per calendar year.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
Ph.D. or professional degree
