Director, Physical AI for Autonomous Discovery

Johnson & Johnson • Spring House, PA

5d • Onsite

About The Position

Johnson & Johnson Innovative Medicine is recruiting a Director, Physical AI for Autonomous Discovery to join its In Silico Drug Discovery team. The preferred location is Spring House, Pennsylvania, with consideration for candidates near Cambridge, Massachusetts. The role may require travel as needed and has no remote option.

The Director will define the Physical AI strategy and lead a focused team developing models for autonomous laboratory experimentation. The position combines AI, robotics, laboratory automation, and scientific reasoning to build systems that perceive, reason, act, learn, recover from errors, and improve experimental outcomes. The role works closely with J&J IT and Data, Data Science & AI partners to deliver a robust and secure agentic platform.

Success includes laboratory systems that detect, diagnose, and recover from execution failures with fewer unplanned interventions; AI-generated hypotheses that explain anomalies and guide follow-up experiments; and closed-loop optimization that improves experimental quality, throughput, reproducibility, and scientific decision-making. Autonomous capabilities should progress safely from AI-assisted automation toward self-improving discovery workflows.

Requirements

• PhD in artificial intelligence, machine learning, robotics, computer science, engineering, computational biology, or a related quantitative field.
• Demonstrated experience developing AI systems that operate in physical or scientific environments.
• Deep expertise in several relevant areas, such as world models, reinforcement learning, Bayesian optimization, causal inference, multimodal AI, robotics, or scientific machine learning.
• Strong software-development skills, including Python and modern machine-learning frameworks.
• Ability to translate scientific and operational requirements into robust, scalable AI models and to communicate across multidisciplinary teams.
• Strong collaboration skills to work 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

• Define and execute the Physical AI strategy, build and lead a high-performing team, and establish a roadmap aligned with scientific priorities and business objectives.
• Develop AI models that understand and reason about instruments, samples, reagents, robotic systems, workflows, and laboratory state.
• Build adaptive experimental optimization capabilities using active learning, Bayesian optimization, reinforcement learning, and multi-objective optimization.
• Create systems for physical error detection and correction, including anomaly recognition, root-cause assessment, workflow replanning, recovery actions, and appropriate human escalation.
• Develop models that generate hypotheses for experimental failures, unexpected results, variability, and irreproducibility, and recommend discriminating follow-up experiments.
• Design agentic and multi-agent systems that coordinate experiment planning, execution monitoring, data interpretation, and decision-making across Design-Make-Test-Analyze cycles.
• Partner with automation, robotics, data science, engineering, and discovery scientists to deploy reliable closed-loop learning in real laboratory environments.
• Embed calibrated uncertainty, safety constraints, monitoring, traceability, and governance into autonomous decision-making.
• Work closely with J&J IT and Data, Data Science & AI partners to deliver a robust and secure agentic platform.

Benefits

• Annual performance bonus, subject to the applicable plan and company discretion.
• Medical, dental, and vision programs.
• Life insurance, short- and long-term disability, business accident insurance, and group legal insurance.
• Consolidated retirement plan (pension) and savings plan (401(k)), subject to eligibility.
• 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Director
• Education Level: Ph.D. or professional degree