Postdoctoral Researchers – Multiphysics Modelling of PVD-Functionalized Battery Electrodes

Unist; Namen; Hybrid; EUR 42,000 - 60,000; Full time

Job summary

University of Namur invites applications for two Postdoctoral Researchers in Battery Modelling and Multiphysics Simulation. The role focuses on building a predictive workflow that links morphology and material properties to battery performance indicators such as capacity, transport properties and cycle degradation.

You will combine modelling, simulation and experimental validation with industrial collaboration.

Qualifications

• PhD in a relevant field with strong modelling background.
• Experience in electrochemical or battery modelling is essential.
• Ability to develop predictive modelling workflows for battery systems.
• Familiarity with plasma-based materials processing is advantageous.

Responsibilities

• Develop a modelling framework linking morphological predictions to battery models.
• Translate insights from Virtual-Coater into input parameters for modelling platforms.
• Conduct numerical and multiphysics simulations with experimental validation.
• Collaborate with industrial partners to transfer technology.

Skills

Electrochemical modelling

Battery systems

Porous-electrode theory

Transport phenomena

Numerical modelling

Multiphysics modelling

Python & C++

Scientific computing

PyBaMM

COMSOL

Education

PhD in electrochemical engineering

PhD in chemical engineering

PhD in materials science

PhD in battery science

Tools

COMSOL

FEniCS

PyBaMM

PyBattMo

Python

C++

MATLAB

Job description

Organisation/Company University of Namur Research Field Physics Researcher Profile Recognised Researcher (R2) Established Researcher (R3) Application Deadline 13 Sep 2026 - 22:00 (UTC) Country Belgium Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No

Offer Description

We are looking for highly motivated Postdoctoral Researchers in Battery Modelling and Multiphysics Simulation to develop a modelling framework linking:

The two successful candidates will investigate how the morphology and physical properties predicted by Virtual-Coater™ can be translated into meaningful input parameters for battery modelling platforms. The ultimate objective is to establish a predictive modelling workflow capable of assessing how PVD functionalization influences battery performance, including:

• capacity;
• ionic and electronic transport;
• polarization and overpotential;
• energy efficiency;
• cycle behaviour and degradation;
• influence of electrode architecture and coating morphology.

A particular objective will be to identify the appropriate level of model complexity required to represent PVD-functionalized electrodes without unnecessarily increasing computational cost.

The work will combine fundamental modelling, numerical simulation and experimental validation, with a strong emphasis on technology transfer to industrial partners.

We are looking for two researchers with PhD in one of the following fields:

electrochemical engineering;
chemical engineering;
materials science;
battery science;
computational materials science;
applied physics;
mechanical engineering;
energy systems;
computational science;
or a closely related discipline.

Essential skills

The candidates should have strong experience in several of the following areas:

electrochemical modelling;
lithium-ion or other rechargeable battery systems;
porous-electrode theory;
electrochemical transport phenomena;
numerical modelling and simulation;
multiphysics modelling;
Python or c++ and scientific computing.

Experience with PyBaMM, PyBattMo, COMSOL, FEniCS , or comparable simulation tools is highly desirable.

A good understanding of battery electrode architecture, including porosity, tortuosity, effective transport properties, interfaces and surface coatings, would be particularly valuable.

Valuable additional experience

Experience in one or more of the following areas would be considered an advantage:

plasma surface functionalization;
electrode/electrolyte interfaces;
battery degradation modelling;
microstructure-resolved modelling;
tomography or image-based electrode modelling;
machine learning/data-driven modelling;
parameter identification and optimization;
scientific software development.

Importantly, direct experience with PVD is not mandatory.

Candidates with strong backgrounds in electrochemical or battery modelling who are interested in developing expertise in plasma-based materials processing are.