Postdoc: Plasma‑Assisted Combustion & AI Kinetics

Vrije Universiteit Brussel; Belgique; Sur place; EUR 28 000 - 44 000; Plein temps

Avantages offerts par ce poste

Homeworking options

Telework allowance 50 €/month

Internet fee 20 €/month

35 days leave

Health insurance

Commuter reimbursement by public交通 or

Campus meals

Sport facilities & discounts

Nursery near campus

Learning opportunities

Résumé du poste

Vrije Universiteit Brussel invites applications for a full-time postdoc position (1 FTE) within the ERC Starting Grant project ESCAPADE on plasma-assisted combustion. The project aims to develop a multi-physics simulation framework combining first-principles modeling, ML, reduced-order methods and CFD to enable predictive tools for low-emission combustion with sustainable fuels.

The researcher will build kinetic models for plasma-assisted combustion, merge ab initio data with experiments, and

Qualifications

• PhD in engineering, chemistry, physics or applied math with a focus on kinetics, combustion, fluids, or plasma.
• Strong numerical simulation and programming experience (Fortran/Python/C++).
• Familiarity with CFD tools such as Ansys Fluent or OpenFOAM is a plus.
• Fluent in written and spoken English; able to work in a team and independently.

Responsabilités

• Contribute to development of next-generation plasma-chemistry models for PAC.
• Integrate ab initio calculations with experimental observations and data-driven approaches.
• Perform numerical simulations and model validation for ammonia/hydrogen fuel blends.

Connaissances

PhD in related field

Numerical simulation

Programming: Fortran/Python/C++

English fluency

Team player

Formation

PhD in engineering/chemistry/physics/applied mathematics

Outils

CFD: Ansys Fluent/OpenFOAM

Description du poste

Vrije Universiteit Brussel invites applications for a full-time postdoc position (1 FTE) within the ERC Starting Grant project ESCAPADE on plasma-assisted combustion. The project aims to develop a multi-physics simulation framework combining first-principles modeling, ML, reduced-order methods and CFD to enable predictive tools for low-emission combustion with sustainable fuels.

The researcher will build kinetic models for plasma-assisted combustion, merge ab initio data with experiments, and