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

Chalmers University of Technology; Göteborgs kommun; On-site; SEK 351,000 - 420,000; Full time

Benefits offered by this job

Employee benefits

Gothenburg location

Job summary

Chalmers University of Technology invites applications for a Doctoral student position in Gothenburg, funded for four years with an option to extend to five years by teaching up to 20%. The project focuses on physics-guided foundation models for multivariate time-series in automotive safety contexts.

You will work with AIXLab@Chalmers and Volvo Group, access industry data, and contribute to publications and validation workflows in real-world settings.

Qualifications

• Master's degree required in CS/EE or equivalent.
• Strong English communication skills.
• Proficiency in Python and PyTorch.
• Experience with large-scale GPU training and reproducible pipelines.
• Ability to formulate research questions and run empirical studies at scale.
• For non-Sweden education, a 4-year bachelor’s degree is accepted.

Responsibilities

• Take courses at an advanced level within the Graduate school of Computer Science and Engineering.
• Develop your own scientific concepts and communicate results in writing and speech.
• Develop reusable modeling frameworks for safety-critical time-series data and contribute to publications.

Skills

Python

PyTorch

Time-series modeling

English proficiency

Research methods

Communication skills

Education

Master's degree (120 credits) in CS/EE or equivalent

Master’s degree (60 credits) magisterexamen

4-year Bachelor’s degree acceptable outside Sweden

Tools

CUDA

Git

Job description

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 Department of Computer Science and Engineering, 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 Division of Computing Science, 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 AIXLab@Chalmers and Volvo Group. You will be joining us at the AIXLab, where we focus on developing AI solutions that are usable and applicable in real-world settings. In addition, you will work closely with engineers and researchers at Volvo Group, with direct access to industrial datasets, simulation environments, and real validation workflows.

About The Research Project

This project advances physics-aware foundation models for time-series data. Here, foundation models refer to reusable, pretrained time-series models that can be adapted across vehicles, driving conditions, and tasks. The primary use case is automotive: predicting vehicle behavior, simulating rare safety-critical scenarios and generating test cases to strengthen validation and reduce physical trials. The techniques are designed to transfer to other safety-critical domains such as healthcare.

Concretely, the research will focus on multivariate vehicle time series such as CAN signals, sensor streams, and simulated state trajectories, with models that integrate physical structure (e.g. dynamics, constraints, conservation laws) into large neural architectures. Physics guidance may include explicit system constraints, inductive biases in model architectures, hybrid simulation learning loops, or loss formulations that encode physical consistency. The work combines forecasting, representation learning, and scenario generation under safety and reliability constraints. The results will support safer automation, fewer failure modes, more efficient testing, and lower energy use.

Who we are looking for

We are particularly interested in candidates who enjoy working at the intersection of theory, data, and real-world systems, and who are comfortable with imperfect, noisy, and safety-constrained data.

The Following Requirements Are Mandatory

• To qualify as a Doctoral student, you must have a Master's degree (masterexamen) of 120 credits or a Master’s degree (magisterexamen) of 60 credits* in Computer Science, Electrical engineering, or equivalent.
• You will need strong written and verbal communication skills in English.
• Strong machine learning fundamentals (probability, statistics, optimization) and strong interest in time-series modeling and physics-guided machine learning.
• Proficiency in Python and modern deep learning frameworks (e.g., PyTorch).
• Strong engineering maturity, including experience with large-scale GPU or cluster-based training, reproducible experiment pipelines, versioned datasets, and systematic evaluation.
• Ability to formulate research questions, run empirical studies at scale.
• for students with an education earned outside of Sweden, a 4-year Bachelor’s degree is accepted.

The Following Experience Will Strengthen Your Application

• Experience with physics-informed machine learning
• Background in foundation models for time-series (forecasting, representation learning)
• Exposure to safety-critical systems, scenario generation, or test coverage for edge cases
• Experience with academic research and publications

What you will do

• Take courses at an advanced level within the Graduate school of Computer Science and Engineering
• Develop your own scientific concepts and communicate the results of your research verbally and in writing
• By the end of the PhD, the candidate is expected to have developed reusable modeling frameworks for safety-critical time-series data. The work should result in publications in top-tier machine learning or applied AI venues and contributions that influence industrial validation pipelines.

Contract terms

• The Doctoral student positions are fully funded from start.
• The position is limited to four years, with the possibility to teach up to 20%, which extends the position to five years.
• A starting salary of 34,550 SEK per month (valid from May 25, 2025).
• Doctoral studies require physical presence throughout the entire study period. A valid residence permit must be presented by the study start date; otherwise the admission may be withdrawn.

What we offer

• As a Doctoral student at Chalmers, you are an employee and enjoy all employee benefits. Read more about working at Chalmers and ourbenefitsfor employees.
• A dynamic and inspiring working environment in the coastal city of Gothenburg.
• Read more about Sweden’s generous parental leave, subsidized day care, free schools, healthcare etc at Move To Gothenburg.

Chalmers is dedicated to improving gender balance and actively works with equality projects, such as the GENIE Initiative for gender equality and excellence. We celebrate diversity and consider equality and inclusion as fundamental aspects of all our activities.

If Swedish is not your native language, Chalmers offers Swedish courses to help you settle in.

Find more general information about doctoral studies at Chalmers here.

We welcome your application no later than October 1st 2026

For Questions, Please Contact

Yinan Yu (about the research project) Email: [e-mail] Carl-Johan Seger (about the application process) Email: [e-mail]

• Chalmers declines to consider all offers of further announcement publishing or other types of support for the recruiting process in connection with this position.***

Chalmers University of Technology in Gothenburg conducts research and education in technology and natural sciences at a high international level. The university has 3100 employees and 10,000 students, and offers education in engineering, science, shipping and architecture.With scientific excellence as a basis, Chalmers promotes knowledge and technical solutions for a sustainable world. Through global commitment and entrepreneurship, we foster an innovative spirit, in close collaboration with wider society.

Chalmers was founded in 1829 and has the same motto today as it did then: Avancez - forward.