Doctoral student in physics-guided foundation model for time-series data

Join us to develop physics-guided, data-driven foundation models for multivariate time-series in safety-critical systems, with a primary focus on automotive applications. You will design predictive and generative models, scale training on real data, and validate in simulation and with industry partners to advance safe, reliable automation.

About us 

The , a joint department of Chalmers and the University of Gothenburg. Our internationally visible research, strong industry links and diverse environment create a collaborative setting where ideas grow into real impact. 

At the , we advance secure and trustworthy software and systems, spanning foundations, programming languages, tools and practical methods that help shape dependable digital infrastructures. 

This project is a collaboration between the and Volvo Group. You will be joining us at the AIXLab, where we focus on developing AI solutions that are usable and applicable in rea...