Insight Global has partnered with a leader in the Life Sciences industry to hire a Contingent Worker Process Modeller to join the Medicine Development and Supply team within the company's R&D Division.
The successful candidate will work cross-modality, be integrated directly on projects, and deliver advanced modelling approaches to accelerate development, increase fundamental understanding, improve risk assessment, and deliver more robust processes, products, and regulatory filings. This includes applying mechanistic, data-driven, and hybrid modelling in process design, control strategy identification, and advanced process monitoring and control for small and large molecule Drug Substance and Drug Product processes.
This individual will translate chemistry equations into code, maintain the code, and deliver documentation. End users include chemists, engineers, and formulators, who will request enhancements that the process modeller must review, prioritize, and execute.
The ideal candidate must have:
* An MSc or PhD in Chemical Engineering / Physical Chemistry or equivalent experience with an emphasis on development and implementation of mechanistic mathematical models.
* Ability to translate mathematical models into computer programs using Matlab, Python, gPROMS, or similar software tools.
* Experience with App Designer in Matlab is imperative.
* An understanding of statistical science and related software tools for experimental design and model interpretation.
* Experience with engineering software such as DynoChem, Aspen, or gPROMS.
* Confident communicator who works well in a team with multiple stakeholders.
It would be a plus if the applicant has the following:
* Previous pharmaceutical industry experience, specifically drug manufacturing.
* Publications in peer-reviewed journals.
* Good lab skills, including designing and executing experimental plans and performing analytical testing.
* Understanding and compliance with company and government Environmental, Safety, and Health requirements.
* Understanding and willingness to comply with GMP requirements, including data integrity and model validation/maintenance.
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