Postdoc “Machine learning for predicting performance decay of batteries”

Job description

As a Belgian and internationally recognized applied research center, VITO aims to accelerate the transition to a sustainable world. The activities of our experienced and driven energy technology team cover cutting-edge technology evolutions, such as battery energy storage systems, renewable systems, electrification of heating, transport & industrial equipment, and further improvement of the energy efficiency of technical applications.

We’re looking for an ambitious postdoctoral researcher to strengthen our sustainable electrical energy devices team and help us to further develop our innovative, next generation battery management system:

Currently Li-ion batteries are widely used in many applications and the management of these batteries is a key element to optimally using this technology. To optimise the performances of a Li-ion battery, the battery management system (BMS) is getting more requirements particularly to increase the battery lifetime and improve its safety. The VITO’s sustainable electric energy devices team is working on developing technologies and services for electrical energy storage that improve overall lifetime, safety and reliability. To further develop the VITO SOX algorithms, we’re looking for a postdoc colleague to develop a machine learning algorithm to detect very early signs of battery performance decay and to predict the probability of battery failure at different time horizons. This study will help the extension possibilities of the current basic battery passport parameter set (while considering timing requirements, sample times, memory wear, ...) in prototype HW. The VITO/EnergyVille labs are equipped with up-to-date infrastructure for cell/battery testing (including safety testing), electric vehicle battery logging, including latest battery management system platform,…


  • You’ll investigate how high-resolution time series battery data can be used to train data-driven machine learning models
  • You’ll compare with physics-based models and investigate whether there is a physical interpretation of the time-series features predicting the battery failure.
  • You will take responsibility for delivering high-quality and timely scientific results
  • You publish your work in high-impact scientific publications, and present your research results in relevant conferences

Job requirements

  • PhD in the context of data science (mathematics, engineering, computer science or similar)
  •  Background in machine learning, ideally including deep learning, and strong interest in interdisciplinary research
  • Experience with recent deep learning frameworks and programming language Python are considered assets
  •  Experience utilising GPU enabled High-Performance Computing environments to be an advantage
  •  Excellent communication, team-working and interpersonal skills
  •  Enthusiasm and great commitment to research


  •  A competitive salary with a range of benefits including allowances, insurances, and a modular vacation package
  • A team of nice colleagues, experts in their fields, who will guide, support and interact with you
  •  Innovation is our asset, so it goes without saying that we offer our employees the opportunity to follow additional training courses and stay up to date in their field of expertise
  • You will be part of an organization with an international reputation, known for its advanced technological research and scientific consultancy