Lower Gwynedd Township, Pennsylvania, United States
At Johnson & Johnson, we believe health is everything. Our strength in healthcare innovation empowers us to build a world where complex diseases are prevented, treated, and cured, where treatments are smarter and less invasive, and solutions are personal. Through our expertise in Innovative Medicine and MedTech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity. Learn more at jnj.com.
As guided by Our Credo, Johnson & Johnson is responsible to our employees who work with us throughout the world. We provide an inclusive work environment where each person is considered as an individual. At Johnson & Johnson, we respect the diversity and dignity of our employees and recognize their merit.
Job Function:
R&D Product DevelopmentJob Sub Function:
R&D Electrical/Mechatronic EngineeringJob Category:
Scientific/TechnologyAll Job Posting Locations:
Spring House, Pennsylvania, United States of AmericaJob Description:
Our expertise in Innovative Medicine is informed and inspired by patients, whose insights fuel our science-based advancements. Visionaries like you work on teams that save lives by developing the medicines of tomorrow.
Join us in developing treatments, finding cures, and pioneering the path from lab to life while championing patients every step of the way.
Learn more at https://www.jnj.com/innovative-medicine
We are searching for the best talent for a Principal Laboratory Automation Scientist to be located in Spring House, PA.
Purpose: The Principal Laboratory Automation Scientist sets the scientific automation architecture for integrated discovery platforms. The role defines how scientific requests, sample states, consumables, automated methods, data provenance, UAT, metadata, exception logic, and user adoption should work across interconnected workcells.
The Principal Scientist will serve as a domain expert for advanced laboratory automation, multi-workcell orchestration, scientific workflow transformation, data provenance, metadata strategy, and AI-ready laboratory execution. They will define the scientific workflow architecture that enables autonomous discovery platforms to generate trustworthy, reproducible, model-usable data.
This role is paired with the Principal Automation and Robotics Engineer. The scientist owns scientific and data architecture for automated workflows; the engineer owns robotics, controls, safety, physical automation, serviceability, and machine architecture. Together they provide the core architectural partnership for self-driving laboratories.
Reference Architecture and Standards
Defining cross-workcell laboratory automation architecture spanning scientific requests, instruments, workcells, sample stores, consumable stores, scheduling layers, data systems, user interfaces, and model feedback loops.
Creating standards for labware, sample identity, reagent identity, consumable identity, state models, method versioning, interface control, recovery logic, run context, data provenance, and operational handover.
Establishing design patterns for request intake, automated worklist generation, queue management, workflow routing, workcell handoffs, exception handling, and data feedback into scientific decision making.
Defining acceptance criteria for nominal workflows, edge cases, failure modes, recovery scenarios, operator interventions, data completeness, and lights-out readiness from a scientific workflow perspective.
Scientific Leadership and Workflow Transformation
Defining scientific and technical requirements for integrated automation platforms supporting biologics discovery, small molecule discovery, protein engineering, screening, analytical sciences, NGS, cell-based assays, biophysics, protein characterization, and translational workflows.
Resolving complex issues spanning scientific method performance, liquid handling, assay suitability, automation constraints, orchestration, data flow, sample logistics, software behavior, facilities constraints, biosafety, and vendors.
Leading cross-functional investigations and improvement programs that increase reliability, scalability, data quality, throughput, scientific adoption, and model feedback utility.
Advising senior partners on workflow maturity, automation readiness, manual versus automated boundaries, standardization opportunities, and scientific risks before major investment decisions.
SDL Enablement and AI-Ready Data
Leading throughput modeling, queue modeling, workflow simulation, digital twin strategy, AI-ready metadata, experimental provenance, sample lineage, failure annotations, and data contracts.
Shaping roadmaps for autonomous execution, physical AI integration, closed-loop experimentation, human oversight, human intervention guardrails, and model feedback.
Defining data quality expectations that connect instrument outputs, sample context, run metadata, environmental context, and scientific interpretation.
Mentoring laboratory automation scientists and influence communities of practice around method robustness, data provenance, automated workflow design, and adoption.
Additional Responsibilities
Support technology evaluations, proof-of-concept studies, workflow readiness assessments, user demonstrations, and vendor evaluations for future automation capabilities.
Contribute to laboratory automation standards, workflow templates, data handoff expectations, training materials, and playbooks.
Support audit, inspection, or quality documentation requests where automated scientific workflows intersect with regulated or quality driven environments.
Participate in lessons learned and continuous improvement activities to improve future automation delivery and adoption.
Education:
A minimum of a Bachelor's degree in Life Science, Analytical Science, Engineering, Computer Science, Laboratory Automation, or a related field is required. An advanced degree is strongly preferred.
Required:
Bachelor's degree with 10+ years, Master's degree with 8+ years, or PhD with 5+ years of relevant laboratory automation, scientific automation, analytical automation, high-throughput discovery, or workcell integration experience.
Demonstrated understanding of laboratory workflows, sample handling, plate/tube formats, assay execution, consumable preparation, run documentation, and data capture.
Hands-on or practical experience with automated liquid handlers or integrated laboratory automation equipment appropriate to the level of the role.
Ability to translate scientific workflows into executable automated methods, worklists, run states, exception pathways, and user-facing procedures.
Working knowledge of sample identity, labware identity, reagent identity, consumable state, barcode traceability, metadata capture, and downstream data requirements.
Ability to collaborate with scientists, automation engineers, IT, data science, AI, EHS, facilities, vendors, and laboratory operations.
Recognized expertise in laboratory automation, integrated workcells, assay automation, workcell orchestration, scientific workflows, and data flow.
Ability to define architecture, standards, interface models, recovery logic, and data requirements across multidisciplinary teams.
Preferred:
Experience with SDLs, digital twins, FAIR data, AI-ready metadata, SiLA 2, OPC UA, APIs, event-driven architectures, microservices, workflow engines, and Tier 1 integrator models.
Experience with biologics discovery, small molecule discovery, protein engineering, high-throughput screening, analytical sciences, NGS, cell-based assays, and model feedback workflows.
Record of scientific or technical innovation through platform deployments, invention disclosures, patents, publications, or external collaborations.
Other:
Travel may be required for vendor assessments, FAT/SAT activities, site visits, system builds, workshops, training, technology scouting, or cross-site deployment support.
This role supports the transition from isolated automation projects to integrated, reliable, AI-native, and ultimately self-driving discovery laboratory systems. The work helps connect scientific intent with robust physical execution, reproducible data, model feedback, and scalable operational capability.
Johnson & Johnson is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, age, national origin, disability, protected veteran status or other characteristics protected by federal, state or local law. We actively seek qualified candidates who are protected veterans and individuals with disabilities as defined under VEVRAA and Section 503 of the Rehabilitation Act.
Johnson & Johnson is committed to providing an interview process that is inclusive of our applicants’ needs. If you are an individual with a disability and would like to request an accommodation, external applicants please contact us via https://www.jnj.com/contact-us/careers, internal employees contact AskGS to be directed to your accommodation resource.
If you are under 18 years of age, you (the candidate) may need to obtain the necessary working papers or other documentation required by state law to start the assignment, as well as get a parent’s consent for the background check.
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