About Basetwo

Basetwo is building the AI layer for pharmaceutical and chemical manufacturing. Our AI-powered digital twin platform helps manufacturers accelerate the journey from lab to commercial production through faster scale-up/tech transfer, and de-risked quality control. Trusted by leading global manufacturers, we're bringing modern AI to one of the world's most complex and impactful industries. Our team combines expertise across chemical engineering, manufacturing, AI, and software to tackle high-impact industrial problems.

The Role

Simulation is at the heart of the Basetwo platform, and our science team is looking to bring on an expert in Process Modelling who will be able to make significant technical contributions to our process simulation engine. The Process Modeller will be responsible for developing mathematical models for the Basetwo platform to solve modelling and control applications in pharmaceuticals and biologics manufacturing. Our ideal candidate will partner with our Customer’s subject matter experts (SMEs) and our Engineering team to deliver product-driven simulation solutions to solve customer challenges.

What You’ll Do

As a Process Modeller, you will: Work closely with customer’s SMEs to understand their process challenges, identify technical requirements and implement advanced modeling solutions Research, develop and validate mathematical models for industrial processes in pharmaceuticals and biologics manufacturing Contribute to product development as it relates to process simulation in collaboration with cross-functional teams, supporting roadmaps and feature iterations based on customer feedback Advocate for best practices among the modeling and simulation team Document research activities and model structure in well-structured product specification documents

This role is a fit for someone whose core expertise is in bioprocesses and pharma/biologics manufacturing. To be successful in this role you will have: Masters or PhD in Chemical Engineering, or a related technical field, with 1-4 years of research experience in modeling, optimization and control of bioprocesses Hands-on experience with metabolic flux analysis (MFA) and/or dFBA is a strong asset Strong foundation in core chemical engineering fundamentals, including chemical kinetics, thermodynamics, and transport phenomena is a must Ability to develop research-grade code in Python leveraging scientific computing libraries Demonstrated track record of starting and leading interdisciplinary research and engineering projects Experience communicating projects to both technical and non-technical audiences, and working on cross-functional teams Product-driven thinking - an ability to map customer pain points to product features