Sr. Scientist, Spectroscopy Lifecycle Support

07 set - Borgo San Michele
7175-Janssen Cilag S.p.A. Legal Entity

At Johnson & Johnson,we believe health is everything. Our strength in healthcare innovation empowers us to build aworld where complex diseases are prevented, treated, and cured,where treatments are smarter and less invasive, andsolutions 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 . 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 Development
- Job Sub Function: R&D; Digital
- Job Category: Scientific/Technology
- All Job Posting Locations: Latina, Italy

Job DescriptionWe are seeking a Sr. Scientist in Spectroscopy and PAT Model Lifecycle Support to join ANVIL, the ApplicatioNs, Validation,



Integration, and Lifecycle group within the Process Science Modelling and Data (PSMD) organization in Manufacturing Science and Technology (MSAT). ANVIL supports the development, validation, deployment, integration, troubleshooting, and lifecycle maintenance of models used to support manufacturing, including models deployed or intended for use in GMP environments. This role will focus on spectroscopic Process Analytical Technology models, with particular emphasis on near-infrared spectroscopy and Raman spectroscopy. The successful candidate will help sustain and develop chemometric models that support product and process understanding, real-time or near‑real‑time decision making, and reliable operation of model‑enabled workflows across manufacturing and laboratory environments. The ideal candidate will bring hands‑on experience with spectroscopy, multivariate modeling, and data analysis, alon

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