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

USA - Pennsylvania - West Point

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 …

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Job Profile

Regions

North America

Countries

United States

Restrictions

Hybrid Hybrid work Hybrid work model On-site Puerto Rico residents only US and Puerto Rico residents only

Benefits/Perks

Bonus eligibility Diverse workplace Equal opportunity employer Flexible work Flexible work arrangements Hybrid work Hybrid work model Inclusion Inclusive environment Insurance Paid holidays Retirement benefits Separation benefits package Sick Days Vacation

Tasks
  • Collaborate with scientists
  • Communication
  • Compliance
  • Drive project outcomes
  • Innovation
  • Manage multiple projects
  • Manage timelines
  • Process development
  • Regulatory filings
  • Troubleshooting
Skills

Biochemical engineering Biologics C CGMP Characterization Chemical Engineering Chemical kinetics Chromatography CMC Commercial Commercialization Communication Compliance Computational Cost Optimization Creativity Data Deployment Development Development and commercialization Digital Digital twins Drug product Drug substance Economics Education Engineering Experimental Facility fit Inclusion Influence Innovation Interpersonal JMP Manufacturing Manufacturing processes Matlab Mechanical Mechanical Engineering Metabolomics Minitab Modeling Modeling and Simulation Open-source tools Operations Optimization Organization Pharmaceutical Pharmaceutical manufacturing PhD Policy Process Characterization Process Development Process modeling Programming Python Quality R Regulatory Regulatory filings Research Research Experience Scale-down Scale-Up Scheduling Simulation Statistical methods Talent Acquisition Teams Tech Transfer Troubleshooting Vaccines

Experience

4-8 years

Education

AS Associate Biochemical engineering Business Chemical Engineering Doctoral Doctoral degree Economics Engineering Graduate Master Master's degree Mechanical engineering MS Related discipline Relevant experience Scientific discipline

Timezones

America/Anchorage America/Chicago America/Denver America/Los_Angeles America/New_York Pacific/Honolulu UTC+0 UTC-10 UTC-5 UTC-6 UTC-7 UTC-8 UTC-9