Our client is an international R&D technology company active in the field of electric energy generation and storage, partnered with the UK -based technology company developing next-generation electric vehicles. You will be a great communicator, hungry to take up the challenge and make a difference in the battery and EV sector. You will be able to work and plan novel research independently and collaborate efficiently within the team. With a deep knowledge of multi-scale modelling and electrochemistry as well as familiarity with experimental characterisation technics.
- We are seeking a creative, adaptable, and motivated battery modelling engineer to create multi-scale physical and reduced-order models of new generation electrochemical energy storage technologies.
- You will also be part of a diverse and international team of scientists and researchers active in the field of new battery technologies.
- You will be working within a thriving team of theorists, modellers and experimental electrochemists and collaborate with academic leaders in the field of multiscale modelling.
- You will be a valuable contributor helping us come up with innovative solutions to the challenges and exciting opportunities we face to improve and transform our societies and the world around us.
- D. in Electrochemistry, Chemical Engineering, Chemistry, Physics or equivalent
- Experience in empirical, Physics-based, and reduced-order modelling for lithium-ion cells
- Experience in creating multi-physics electrochemical system modelling, thermal, and general transport- reaction processes.
- Knowledge of the degradation mechanisms causing energy loss and power fade in lithium-ion batteries.
- Expertise in battery management systems, charging protocols, systems integration of batteries and electrochemical systems.
- Proficiency with Python, and with packages like Scikit-learn and Keras, C/C++, MATLAB to process, visualize, analyse and model data.
- Proficiency with energy storage modelling software like COMSOL, PyBAMM, Ansys
- Proficient in battery and electrochemical system test methods, data acquisition and data handling methods, data science/AI-based models for batteries and electrochemical systems.