Process Modelling Engineer

Process Modelling Engineer

Series B Med Tech (£20M+ Raised)

📍 Cambridge or Oxford (Hybrid)

We’re partnering with a fast-growing Series B Med Tech developing next-generation bioprocessing technology that is reshaping how advanced therapies are designed, scaled, and manufactured.

With over £20M raised from top-tier investors, the company is now expanding its core R&D and digital engineering team.

As a Process Modelling Engineer, you’ll build the mechanistic and hybrid models that power their platform. Accelerating development, improving process robustness, and enabling data-driven decision making across the full bioprocess lifecycle.

This Series B Med Tech is unifying bioprocess engineering, computational modelling, and automation to tackle one of the biggest bottlenecks in biotech: how to scale complex biological systems reliably and efficiently.

Their platform integrates mechanistic simulations, ML-driven predictions, and automated workflows, giving bioprocess teams the tools to accelerate development, reduce variability, and shorten time to clinic.

With teams in Cambridge and Oxford, they’re building at the intersection of engineering, biology, and software and looking for exceptional people who want to shape the next wave of bioprocess innovation.

• Build mechanistic and hybrid models across upstream and downstream bioprocesses.
• Develop system-level flowsheet and unit operation models.
• Run sensitivity, identifiability, and optimisability studies to guide experimental design and scale-up.

• Create modular, intuitive modelling workflows used across the company’s platform.
• Work closely with software engineers to convert models into scalable, web-based tools.
• Build user-facing applications that make complex models accessible to non-experts.

• Automate model execution, validation, and reporting pipelines.
• Use AI and modern engineering practices to streamline and standardise codebases.
• Connect models to diverse datasets—structured (SQL, Databricks, Snowflake) and unstructured (e.g., Excel, lab exports).

• STEM MSc or PhD

• Strong background in transport phenomena, systems modelling, and process engineering.
• Solid experience with Python and scientific / optimisation tools (Num Py, Sci Py, pandas, CasADi, Pyomo).

• Experience in biotech, pharma, CDMO, or advanced therapy development.
• Exposure to process development, modelling-driven scale-up, or digitalisation initiatives.

• CFD knowledge (e.g., OpenFOAM).
• Familiarity with machine learning and data engineering workflows.
• Publications in modelling, simulation, systems engineering, or digital twins.

• Analytical, curious, and detail-driven.
• Strong communicator who can explain complex ideas clearly.
• Collaborative mindset with a pragmatic, problem-solving approach.

If this sounds like you, you'll fit right in.

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