Process Modelling & Simulation Lead - Synthetic Molecules

About the role

Roche is looking for a Process Modelling & Simulation Lead to head its Modelling & Simulation Centre of Excellence for Synthetic Molecules Technical Development (PTDC). The role defines the strategy, vision, roadmap, standards and governance for modelling and simulation across PTDC, leading a cross-departmental community of 20+ experts and influencing senior leaders across an organization of 700+ employees.

Key responsibilities

• Define the strategy, vision, roadmap, standards and governance for M&S across PTDC, and lead a cross-departmental community of 20+ experts.
• Influence and guide senior leaders, propose innovative ways of working and prioritize high-impact applications.
• Shape end-to-end M&S strategy across Drug Substance and Drug Product lifecycles, from early lab development through scale-up, technology transfer and commercial manufacturing.
• Act as senior technical authority on complex development challenges, optimizing processes, supporting experimental design and refining scale-up/scale-down models.
• Build validated model libraries, digital twins, scale-up tools and self-service applications.
• Coach and mentor scientists and engineers, and connect Roche with universities, research consortia and technology vendors.
• Influence high-value technology investments and maintain governance over a six-figure software portfolio.

Required profile

• Master's degree or PhD in Chemical Engineering, Pharmaceutical Sciences, Chemistry or a closely related discipline.
• 12+ years of professional experience in process engineering and M&S in the pharmaceutical or science-based industries.
• Proven matrix leadership and stakeholder influence across PTD and R&D without direct formal authority.
• Fluent English, written and spoken.

Required skills

• Hands-on experience with modelling platforms such as gPROMS/gWAP and Dynochem, and programming in Python and MATLAB.
• Knowledge of scale-up/down dynamics and pharmaceutical manufacturing phenomena.
• Understanding of classical mechanistic modelling, CFD (COMSOL, M-Star), model-based process control, PAT, and emerging AI/ML approaches including digital twins and agentic AI.