Uppsala University, a leading research institution in Sweden, is inviting applications for a postdoctoral position in unsupervised machine learning for battery timeseries data. The position is based at the Department of Information Technology, specifically within the Division of Systems and Control, which is renowned for its interdisciplinary research integrating control theory, machine learning, optimization, and network science. The research will focus on developing interpretable unsupervised machine learning methods to extract dynamical models of battery degradation from multimodal timeseries data, including high-frequency acoustic emission and electrochemical measurements.

This project is part of the COMPEL initiative, a strategic Swedish government program aimed at advancing the electrification of the transport sector and battery development. The successful candidate will join a vibrant, international research environment and collaborate with experts in machine learning and battery sensing, including Assistant Professors Jens Sjölund and Leiting Zhang. The research aims to move beyond black-box prediction by learning low-dimensional latent representations that capture underlying physical processes in batteries, enabling new diagnostic capabilities for real-time battery monitoring.

Applicants should have a PhD in machine learning, automatic control, system identification, signal processing, applied mathematics, battery systems, or a related field. Strong technical skills in machine learning, optimization, probabilistic modelling, and programming are required, along with a proven publication record and proficiency in English. The position is fully funded for two years, with a competitive salary and the possibility of teaching up to 20% of the time. The application deadline is February 2, 2026, and the expected start date is March 1, 2026, or as agreed.

To apply, candidates must submit a CV, grade documents, publication list, up to five selected publications, a research statement, a proposal for future activities, and contact information for two references through Uppsala University's recruitment system. For further information, contact Assistant Professors Jens Sjölund ([email protected]) or Leiting Zhang ([email protected]). This is an excellent opportunity for researchers interested in interdisciplinary work at the intersection of machine learning, battery technology, and data-driven modelling.