Postdoc position in AI-Driven Modelling of High-Entropy Electrolytes Full-time NEW

Postdoc Position in AI-Driven Modelling of High-Entropy Electrolytes

Uppsala University, Department of Chemistry – Ångström Laboratory

The project focuses on modeling at the molecular level of several different types of high-entropy electrolytes for application in both lithium and sodium batteries. The goal is to understand how different design and material choices link to structure, dynamics and performance.

A special focus is on solvent-free electrolytes based on salt melts. The methods are primarily molecular dynamics simulations and small DFT calculations, but the software COSMO-RS may also be used.

The project combines computational chemistry, molecular modelling, and artificial intelligence. A central part of the work is to develop and apply modern AI and machine learning methods to explore, understand, and optimize high-entropy electrolytes.

The postdoctoral fellow will be part of Prof. Patrik Johansson's new research group at Uppsala University, a part of the research environment Ångström Advanced Battery Centre (ÅABC). This fundamental but application-inspired research project is funded by the Swedish Research Council within the framework of a Distinguished Professor Grant for “Next Generation Batteries”.

The main tasks of a postdoctoral fellow are to conduct research. They may also include teaching, up to 20% of the working time, and supervision of and collaboration with doctoral students and thesis workers.

Doctoral degree in chemistry, physics or materials or an international degree deemed equivalent. The degree must be completed no later than the time the employment decision is made.

Normally, the degree should have been awarded within the past three years, calculated from the application deadline. In special circumstances, the degree may have been awarded earlier. Special circumstances refer to leave due to illness, parental leave, elected positions in trade union organizations, and similar situations.

Applications are primarily assessed based on the applicant's ability to conduct independent research and their scientific excellence. The quality of each individual scientific work carries more weight than the number of publications.

Consideration will also be given to good collaborative skills, drive and independence, and how the applicant's experience and skills complement and strengthen ongoing research within the department, and how they stand to contribute to its future development.

The candidate must have:

• Excellent written and oral English skills
• Documented experience in modelling at the molecular level
• Documented experience in artificial intelligence and machine learning for materials science applications.

Desirable qualifications:

• Documented experience of research within electrolytes and modern batteries is an asset.
• Experience in the application of artificial intelligence and machine learning in battery research is highly desirable.

The employment is a temporary position of two years according to central collective agreement. Scope of employment 100%. Starting date as agreed. Placement: Uppsala.

For further information about the position, please contact: Torbjörn Fängström, +46 18-471 33 65, torbjorn.fangstrom@kemi.uu.se

Please submit your application by October 1 2026, UFV-PA 2026/2547.