Associate Principal Scientist (Computational), Process & Product Modeling – Large Molecules Full-time

Associate Principal Scientist

Join our Company's Process & Product Modeling Team as an Associate Principal Scientist, where you will lead the development of advanced computational models that accelerate the development and commercialization of biologics, vaccines, sterile liquids, and other large-molecule therapies. This role offers a unique opportunity to apply your expertise to optimize complex manufacturing processes and directly impact patient health worldwide.

The initial focus of this role will be on downstream processes such as mechanistic chromatography modeling, filtration, end-to-end process flowsheets, and engineering models (mass, momentum, energy transport, chemical/biochemical reaction kinetics, digital twins, etc.) applicable to biologics and vaccines. Experience in these modeling methods is desired, but candidates with willingness and capability to grow in these areas are also encouraged to apply. In addition, the successful candidate will have opportunities to grow their knowledge into new areas, including model-based process controls, plant and process-economics (including facility fit, cadence, scheduling, and cost optimization), bioreactor kinetics and metabolomics, population balance models, data driven models, digital twin and other modeling approaches.

Responsibilities:

• Collaborate closely with multidisciplinary scientists and engineers to create end-to-end predictive models that support drug substance and drug product manufacturing operations.
• Develop and apply mechanistic and data-driven models especially chromatography, and including filtration, process flowsheets, process economics, and “digital twins” to solve real-world manufacturing challenges encountered during commercialization of new biologics and vaccines.
• Drive innovation by championing computational tools that reduce costs, minimize experimental batches, shorten timelines, and improve product quality and process robustness. Communicate complex modeling insights clearly to project teams and leadership, translating results into actionable experimental and manufacturing strategies.
• Lead the deployment of computational solutions using commercial software, open-source tools, and proprietary models you help develop.
• Work independently with minimal supervision, managing multiple projects and timelines effectively.
• Present your work at internal meetings, scientific conferences, and contribute to publications.
• Lead collaborations with external partners such as universities, research organizations, and contract manufacturing organizations (CMOs/CDMOs) to advance modeling capabilities.

Locations: West Point, PA | Rahway, NJ | Greater Dublin Area, Ireland

Required Qualifications:

• PhD with 4+ years or MS with 8+ years of relevant experience in Chemical, Biochemical, Mechanical, Biological, Pharmaceutical Engineering, or related fields.
• Strong research background in computational modeling applied to large-molecule biologics manufacturing.
• Expertise in one or more of the following: mechanistic chromatography modeling (preferred), end-to-end flowsheet/digital twin modeling, plant/process economics, bioreactor kinetics, population balance models, engineering transport models, or data-driven modeling.
• Experience with relevant software tools (e.g., GoSilico, CADET, SuperPro, ASPEN Plus, gPROMS, BioSolve, Dynochem). Proficiency in programming languages such as Python (preferred), Matlab, C/C++, or R.
• Excellent organizational, interpersonal, and communication skills.
• Proven ability to work effectively in cross-functional teams.
• Industrial or relevant research experience with biologics, vaccines, or sterile liquid manufacturing processes. Candidate with strong modeling and computational experience in other process industries will also be considered.

Preferred Qualifications:

• Demonstrated success in applying modeling outcomes in commercial and cGMP environments.
• Familiarity with regulatory filings (BLAs, NDAs) and Chemistry, Manufacturing, and Controls (CMC) processes.
• Experience with high-performance computing.
• Strong publication, presentation, or patent record.
• Knowledge of statistical software (Minitab, JMP) and other related modeling techniques such as machine learning (ML) or artificial methods (AI), computational fluid dynamics (CFD), etc.