Process Modelling Engineer

CozensWain; Greater London; Hybrid; GBP 60,000 - 80,000; Full time

Job summary

A growing Series B MedTech company is seeking a Process Modelling Engineer to develop mechanistic and hybrid models for bioprocessing. You will create simulation workflows, automate processes, and leverage data integration to enhance efficiency in biotech operations. The ideal candidate holds a STEM MSc or PhD and has a solid grounding in transport phenomena and systems modelling. This hybrid opportunity is based in Cambridge or Oxford, offering a dynamic and collaborative work environment.

Qualifications

• Strong background in transport phenomena, systems modelling, and process engineering.
• Solid experience with Python and scientific/optimisation tools.

Responsibilities

• Build mechanistic and hybrid models across upstream and downstream bioprocesses.
• Develop system-level flowsheet and unit operation models.
• Create modular, intuitive modelling workflows used across the company’s platform.

Skills

Transport phenomena

Systems modelling

Process engineering

Python

NumPy

SciPy

pandas

CasADi

Pyomo

Education

STEM MSc or PhD

Job description

Process Modelling Engineer

Series B MedTech (£20M+ Raised)

📍 Cambridge or Oxford (Hybrid)

About the Opportunity

We’re partnering with a fast-growing Series B MedTech 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.

About the Company

This Series B MedTech 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.

What You’ll Do

Modelling & Simulation

• 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.

Digital Workflow Development

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.

Automation & Data Integration

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).

What You’ll Bring

Education

STEM MSc or PhD

Technical Skills

Strong background in transport phenomena, systems modelling, and process engineering.

Solid experience with Python and scientific / optimisation tools (NumPy, SciPy, pandas, CasADi, Pyomo).

Preferred Experience

Experience in biotech, pharma, CDMO, or advanced therapy development.

Exposure to process development, modelling-driven scale-up, or digitalisation initiatives.

Bonus Skills

CFD knowledge (e.g., OpenFOAM).

Familiarity with machine learning and data engineering workflows.

Publications in modelling, simulation, systems engineering, or digital twins.

Soft Skills

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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