Job Description
The Process & Product Modeling Team in our Company Manufacturing Division seeks an experienced Associate Principal Scientist who will develop and utilize advanced computational models to support the development and commercialization of biologics, vaccines, sterile liquids, and other large-molecules modalities. In this role, you will build and apply predictive tools for drug substance (upstream, downstream, and conjugation) and drug product manufacturing unit operations using a variety of process-modeling tools.
As a potential candidate, you should have advanced graduate degree(s) in an engineering or closely-related scientific discipline, and industrially-relevant experience in process modeling and simulation applicable to large molecules. You should have expertise in one or more of the following modeling areas: mechanistic chromatography modeling, end-to-end flowsheets and digital twins, model-based process controls, plant and process-economics (including facility fit, cadence, scheduling, and cost optimization), bioreactor kinetics and metabolomics, population balance models, engineering models (mass, momentum, energy transport, chemical/biochemical reaction kinetics, etc. applicable to biologics and vaccines), data driven models, and other modeling methods. Your experience should reflect the application of advanced computational tools to address relevant pharmaceutical manufacturing challenges.
This position is located at West Point (PA, USA), Rahway (NJ, USA), greater Dublin area (Ireland), or remote.
Roles and Responsibilities
- Work collaboratively with our Company scientists and engineers to develop end-to-end modeling solutions that will help with development, commercialization, and troubleshooting of large-molecule unit operations.
- Using modeling solutions, support process development, process characterization, scale-up, scale-down, tech-transfer, and troubleshooting. Champion the use of computational techniques to influence project teams and the organization. Drive tangible outcomes: reduced costs, fewer experiments and batches, faster timelines, improved quality and process robustness.
- Demonstrate creativity in solving complex, physical/biochemical problems faced during industrial manufacturing. Lead the development and deployment of computational tools, using a combination of commercial software, open-source tools, and in-house models (that you may have created).
- Work independently with minimal supervision. Interact directly with project teams to identify modeling opportunities, and propose and execute modeling solutions to complex, experimental problems.
- Communicate effectively with project teams on the status of workstreams and manage timelines; translate modeling results to actual, experimental outcomes in projects. Present at internal and external forums (conferences, publications).
- Lead external collaborations (with universities, research organizations, etc.). Work independently with internal and external partners (e.g., CMOs, CDMOs, vendors) to develop novel modeling solutions to support tech transfer.
Required:
- Master’s degree (MS / M.S.) with minimum of 8 years or Doctoral degree (PhD / Ph.D.) with a minimum of 4 years of relevant experience, preferably in Chemical Engineering, Biochemical Engineering, Mechanical Engineering, Biological Engineering, Pharmaceutical Engineering, or any other closely-related discipline. Must have research experience in a computational specialization.
- Expertise with one or more computational techniques relevant to large-molecules modeling: chromatography modeling, end-to-end flowsheet modeling, plant modeling (facility fit, cadence, scheduling), process economics and optimization. Candidates with expertise in bioreactors, engineering modeling, mixing, chemical & biochemical kinetics, data-driven and other modeling approaches also encouraged to apply.
- Experience in any of the following software packages or similar (not a comprehensive list): GoSilico, CADET, SuperPro, ASPEN Plus, gPROMS, BioSolve, Dynochem.
- Proficiency in programming in at least one standard language: Python, Matlab, C/C++, R, etc.
- Excellent organization skills and be able to manage multiple projects simultaneously. Excellent interpersonal skills and ability to work in cross-disciplinary teams.
- Excellent communication skills, verbal and written.
- Industrial or relevant research experience with large-molecule modalities (biologics, vaccines, sterile liquids) and their manufacturing processes.
Preferred:
- Track record of successful implementation of modeling outcomes in the commercialization and cGMP environments is highly desired. Familiarity or experience with regulatory filings (BLAs, NDAs) and CMC processes preferred.
- Experience with high-performance computing.
- Track record of publications, presentations, and/or patents. Awareness of latest modeling developments and advances in candidate’s area of expertise.
- Familiarity with statistical methods and packages (e.g., Minitab, JMP, etc.); familiarity with other modeling methods relevant to large molecules, e.g., computational fluid dynamics (CFD).
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