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Giovanni Samaey

Top university

1 month ago

Postdoc in Interacting Particle Methods for Bayesian Inversion with Model Error KU Leuven in Belgium

Degree Level

Postdoc

Field of study

Computer Science

Funding

Available

Deadline

Expired

Country flag

Country

Belgium

University

KU Leuven

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Where to contact

Official Email

Keywords

Computer Science
Mathematics
Numerical Analysis
Stochastic Processes
Computational Science
Electrophysiology
Computational Mathematics
Monte Carlo Simulation
Sampling Methods
Optimisation
Pde
Inverse Problem
Applied Mathematic

About this position

NUMA, a research section within the Department of Computer Science at KU Leuven, is seeking a postdoctoral researcher to join their team in the field of interacting particle methods for Bayesian inversion with model error. NUMA specializes in numerical analysis and applied mathematics, focusing on the development of numerical algorithms and software for large-scale scientific and engineering problems. The group is internationally recognized and offers a vibrant research environment with 12 permanent staff and around 60 PhD and postdoctoral researchers.

The successful candidate will contribute to advancing Bayesian computational methods for inverse problems, particularly those involving partial differential equations (PDEs) with high-dimensional parameters and state variables. The project aims to increase the validity of interacting particle methods for Bayesian inversion by explicitly incorporating model error into the likelihood evaluation. A key application area is the inference of parameters in phenomenological models for cardiac electrophysiology, benefiting from collaboration with the Department of Cardiovascular Imaging and Dynamics at KU Leuven.

Candidates should hold a PhD in Mathematical Engineering, Applied Mathematics, or a closely related field. Essential qualifications include a strong background in numerical methods for differential equations, simulation of stochastic processes, and/or optimization. Experience with Bayesian sampling methods and scientific software programming is highly valued, and familiarity with cardiac electrophysiological modeling is considered a plus. Excellent English proficiency and strong communication skills are required.

The position offers a high-level international research environment, opportunities for professional development, and a supportive team. Funding is secured for two years, with the possibility of a third year depending on funding and scientific progress. The salary is competitive. KU Leuven is committed to diversity, inclusion, and equal opportunity.

To apply, candidates should submit a letter of motivation, CV, copies of university diplomas and transcripts, and contact information for 1-2 references. Applications are reviewed on a rolling basis until the position is filled, with a formal deadline of February 28, 2026. For further information, contact Prof. dr. ir. Giovanni Samaey at [email protected]. Apply via the official KU Leuven jobsite.

Funding details

Available

What's required

Candidates must hold a PhD in Mathematical Engineering or Applied Mathematics (or equivalent). A solid background in numerical methods for differential equations, simulation of stochastic processes, and/or optimization is required. Specific experience with sampling methods for Bayesian inference is highly appreciated. Experience with cardiac electrophysiological modeling is a plus. Candidates should have experience with programming of scientific software. Excellent proficiency in English and good communication skills, both oral and written, are required.

How to apply

Submit your application including a letter of motivation, curriculum vitae, university diploma copies and transcripts, and names and contact information of 1-2 references. Apply via the provided KU Leuven jobsite link. Applications are considered as soon as received and the position will close once filled.

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