Distinguished Scientist or fellow Mechanistic Modeling & AI

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 https://www.jnj.com

Job Function:

R&D Product Development

Job Sub Function:

R&D Digital

Job Category:

Scientific/Technology

All Job Posting Locations:

Titusville, New Jersey, United States of America

Job Description:

Johnson & Johnson Innovative Medicine is (IM) recruiting for a Distinguished Scientist or Fellow Mechanistic Modeling & AI to join our Process Science, Modeling and Data (PSMD) team within Manufacturing, Science and Technology (MSAT).
 

Our expertise 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.
 

Are you a pragmatist and an entrepreneur with a strong sense for prioritization? Apply now for this unique opportunity!
 

The person we are looking for is a versatile, and highly-motivated member of our established, multi-functional and international team. As a key technical resource, they will design, develop and deploy modeling solutions within the manufacturing environment of our growing portfolio of biotherapeutics, synthetics, and advanced therapies products. They will also guide and mentor those around you, shaping our advanced manufacturing roadmap. Come join our team!
 

Key Responsibilities:

• You will act as individual contributor supporting high priority modeling requests (e.g., for root cause investigations) coming from senior leadership in supply chain. As such, you will directly interact with these customers, explaining rationale and outcomes.

• As a designer and leader of cross-platform, strategic modeling innovation programs, you will work with business leaders and IT to incorporate next-generation digital solutions into MSAT’s ways of working.

• You will scout and benchmark new tools, modalities, and talent. As our premiere modeling authority, you will represent PSMD and the larger MSAT organization at conferences and industry events.

• You will be a technical mentor, guide, and support for the entire modeling organization; working closely with our model maintenance and standards lead to ensure the highest quality in our model solutions and the consistent adoption of standards.
   

Qualifications

Education:

• Minimum of Masters or equivalent degree in a Scientific domain.

• Education in a technical field related to pharmaceutical manufacturing, such as Chemical Engineering, Bioengineering, Biomedical Engineering, Chemistry, or a similar quantitative scientific field is preferred.

Experience and Skills:

Required:

• An outstanding track record of delivering impactful solutions, using both mechanistic modeling and AI methodologies in manufacturing settings. Familiarity with a variety of methodologies and approaches in both domains, knowing when to use which or when to combine.

• An understanding of pharmaceutical manufacturing processes and the associated unit operations, an appreciation for the impact of GxP regulation on modeling

• Strong background in at least one scientific programming language (e.g., python, Matlab, R, julia, ...) and familiarity with other tools (e.g., SIMCA, Ansys suite, ...). Excellent understanding of software development standards (e.g., version control, CI/CD).

• Outstanding skills in scientific communication and excellent with effective visual display of quantitative information. Able to author and review highly sophisticated modeling-related documents (e.g., global guidelines and procedures).

Preferred:

• Sound grasp of computerized systems validation/assurance and in- and external standards regarding model risk categorization.

• Familiarity with optimization and process control concepts such as model predictive control, reinforcement learning, and state estimators.

• A history of publications in r