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 / 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 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).
NOTICE FOR INTERNAL APPLICANTS
In accordance with Managers' Policy - Job Posting and Employee Placement, all employees subject to this policy are required to have a minimum of twelve (12) months of service in current position prior to applying for open positions.
If you have been offered a separation benefits package, but have not yet reached your separation date and are offered a position within the salary and geographical parameters as set forth in the Summary Plan Description (SPD) of your separation package, then you are no longer eligible for your separation benefits package. To discuss in more detail, please contact your HRBP or Talent Acquisition Advisor.
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Effective September 5, 2023, employees in office-based positions in the U.S. will be working a Hybrid work consisting of three total days on-site per week, Monday - Thursday, although the specific days may vary by site or organization, with Friday designated as a remote-working day, unless business critical tasks require an on-site presence.This Hybrid work model does not apply to, and daily in-person attendance is required for, field-based positions; facility-based, manufacturing-based, or research-based positions where the work to be performed is located at a Company site; positions covered by a collective-bargaining agreement (unless the agreement provides for hybrid work); or any other position for which the Company has determined the job requirements cannot be reasonably met working remotely. Please note, this Hybrid work model guidance also does not apply to roles that have been designated as “remote”.
The Company is required to provide a reasonable estimate of the salary range for this job in certain states and cities within the United States. Final determinations with respect to salary will take into account a number of factors, which may include, but not be limited to the primary work location and the chosen candidate’s relevant skills, experience, and education.
Expected US salary range:
$135,500.00 - $213,400.00Available benefits include bonus eligibility, long term incentive if applicable, health care and other insurance benefits (for employee and family), retirement benefits, paid holidays, vacation, and sick days. A summary of benefits is listed here.
San Francisco Residents Only: We will consider qualified applicants with arrest and conviction records for employment in compliance with the San Francisco Fair Chance Ordinance
Los Angeles Residents Only: We will consider for employment all qualified applicants, including those with criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance
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Merck & Co., Inc., Rahway, NJ, USA, also known as Merck Sharp & Dohme LLC, Rahway, NJ, USA, does not accept unsolicited assistance from search firms for employment opportunities. All CVs / resumes submitted by search firms to any employee at our company without a valid written search agreement in place for this position will be deemed the sole property of our company. No fee will be paid in the event a candidate is hired by our company as a result of an agency referral where no pre-existing agreement is in place. Where agency agreements are in place, introductions are position specific. Please, no phone calls or emails.
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Hybrid Hybrid work Hybrid work model On-site Puerto Rico residents only US and Puerto Rico residents only
Benefits/PerksBonus 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
- Communicate modeling results
- Communication
- Compliance
- Develop computational models
- Drive project outcomes
- Innovation
- Lead modeling solutions
- Manage multiple projects
- Manage timelines
- Present at forums
- Process development
- Regulatory filings
- Support process development
- Troubleshooting
Biochemical engineering Biochemical kinetics Biologics Bioreactor kinetics C CGMP Characterization Chemical Engineering Chemical kinetics Chromatography Chromatography modeling CMC Commercial Commercialization Communication Compliance Computational Computational modeling Computational tools Cost Optimization Creativity Data Data driven models Deployment Development Development and commercialization Digital Digital twins Drug product Drug substance Economics Education Engineering Engineering models Experimental Facility fit Inclusion Influence Innovation Interpersonal JMP Manufacturing Manufacturing processes Matlab Mechanical Mechanical Engineering Metabolomics Minitab Model-based process controls Modeling Modeling and Simulation Open-source tools Operations Optimization Organization Pharmaceutical Pharmaceutical manufacturing PhD Policy Population balance models Process Characterization Process Development Process economics 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
Experience4-8 years
EducationAS Associate Biochemical engineering Biological engineering Business Chemical Engineering Doctoral Doctoral degree Economics Engineering Graduate Master Master's degree Mechanical engineering MS Pharmaceutical engineering Related discipline Relevant experience Scientific discipline
TimezonesAmerica/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