Postdoc position in AI and Machine Learning Electromobility

Postdoc Position in AI and Machine Learning for Electromobility

Do you want to contribute to the future of AI-driven electric transport systems? Join our research group to develop advanced machine learning methods for electromobility, focusing on energy-aware coordination of electric vehicle fleets to support resilient transport systems during emergency evacuations.

The project focuses on the energy-efficient coordination of electric vehicle (EV) fleets for resilient transport systems during emergency evacuations. Climate change is increasing the frequency and severity of natural disasters, including floods, wildfires, and extreme weather events, making efficient large-scale evacuation planning increasingly important. At the same time, the transport sector is undergoing a rapid transition toward electrification. While EVs are central to achieving climate-neutral mobility, most existing evacuation planning methods still assume conventional fuel vehicles and do not account for EV-specific challenges, such as limited battery capacity, variable energy consumption, charging infrastructure availability, recharging requirements, and interactions with the electricity grid.

This multifaceted gap presents a significant challenge for designing evacuation strategies that remain effective in future electrified transport systems. The project aims to develop novel AI methods for coordinating fleets of EVs during large-scale emergency evacuations under energy and infrastructure constraints. To address this challenge, the research will leverage reinforcement learning, deep learning, and generative AI, and evaluate against the research front in mathematical optimization strategies, to enable efficient, robust, and adaptive evacuation planning.

The following requirements are mandatory:

• A doctoral degree in computer science, artificial intelligence, applied mathematics, physics, electrical engineering, or a closely related field. This eligibility requirement must be met no later than the time the employment decision is made.
• Strong research experience in AI, machine learning and optimization with publications in top-tier venues.
• Strong programming skills, preferably in Python and PyTorch.
• Strong written and verbal communication skills in English.

The following experience will strengthen your application:

• Publications in A
  * venues in AI, machine learning, and data science.
• Experience with reinforcement learning, Markov decision processes and/or control theory.
• Experience in fundamental and applied AI/machine learning research.

What you will do:

• Propose, develop, and evaluate advanced machine learning models, including reinforcement learning methods, for the energy-aware coordination of EV fleets.
• Publish high-quality scientific papers in relevant leading venues.
• Contribute to the supervision of master's and PhD students.

The position is a temporary full-time employment for two years, starting on January 1, 2027. The position requires physical presence throughout the entire employment. A valid residence permit must be presented by the start date, otherwise the offer may be withdrawn.

As a postdoc at Chalmers, you are an employee and enjoy all employee benefits. Read more about working at Chalmers and our benefits for 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.

The application should be written in English be attached as PDF-files, as below. Maximum size for each file is 40 MB. Please note that the system does not support Zip files.

A comprehensive CV, including a complete list of publications. Details of previous teaching and superv experience. A brief introduction about yourself. A summary of your previous research fields and key research outcomes. An outline of your future goals and research focus.

We welcome your application no later than September 15, 2026. For questions please contact:
Professor Morteza Haghir Chehreghani morteza.chehreghani.