Sr Scientist Process Science Modeling

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

Job Function:

R&D Product Development

Job Sub Function:

R&D Digital

Job Category:

Scientific/Technology

All Job Posting Locations:

Leiden, South Holland, Netherlands, Ringaskiddy, Cork, Ireland, Schaffhausen, Switzerland

Job Description:

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 Johnson & Johnson.

Johnson & Johnson's Manufacturing Science and Technology (MSAT) Advanced Manufacturing team is seeking a versatile and driven Senior Process Science Modeling Scientist for our Process Science Modeling and Data (PSMD) group. This role is critical in developing and deploying advanced mathematical models to optimize and enhance biopharmaceutical manufacturing processes. The candidate will bring a strong background in process modeling, optimization, and data-driven decision making, with a passion for innovation in the pharmaceutical industry.

Qualifications

• PhD or equivalent experience in Chemical Engineering, Bioengineering, or related subject area, or

• MSc in Chemical Engineering, Bioengineering, or related field with proven experience in the pharmaceutical industry

Required Skills & Experience

• Demonstrated background in Model Predictive Control, with relevant publications

• Expertise in mathematical optimization, including Nonlinear Programming (NLP), with solvers such as Ipopt and Baron, and using modeling libraries such as Pyomo

• Some knowledge of Mixed-Integer Linear Programming (MILP) and discrete-event simulation tools and frameworks, including SIMIO and SimPy is desirable

• Familiarity with mechanistic or hybrid modeling approaches for unit operations in pharmaceutical manufacturing

• Strong Python programming skills for model development, data analysis, and workflow automation

• Solid foundation in statistics and familiarity with machine learning models applied to process science

Key Responsibilities

• Develop, validate, and deploy mathematical models to improve pharmaceutical manufacturing processes

• Engage with colleagues across engineering, manufacturing, and data science teams to understand challenges and deliver impactful solutions

• Design and implement technical roadmaps for innovation initiatives within the PSMD team

• Participate actively in research discussions, both internally and with academic partners, to develop knowledge exchange and collaborative innovation

• Collaborate with internal team members to identify and address process improvement opportunities

About PSMD at J&J MSAT Advanced Manufacturing

The PSMD group at Johnson & Johnson MSAT Advanced Manufacturing is dedicated to advancing pharmaceutical process science through innovative modeling, simulation, and data analytics. We strive to deliver robust solutions that drive efficiency, quality, and innovation across our manufacturing network.

Required Skills:

Preferred Skills:

Analytical Reasoning, Critical Thinking, Data Savvy, Digital Fluency, Digital Strategy, Engineering, Product Design, Product Development, Product Improvements, Product Portfolio Management, Report Writing, Research and Development, Safety-Oriented, SAP Product Lifecycle Management, Statistics, Technical Credibility, Technologically Savvy

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