Postdoc Probabilistic AI for Flexible Energy Management Solutions

Job Description

Are you interested in developing cutting-edge Bayesian AI agents? In this postdoc you will design Bayesian agents that predict and advise on flexible energy usage. By reasoning with uncertainty, these agents contribute to the reliability of energy networks in the Netherlands. This research requires a multidisciplinary approach, combining probabilistic (Bayesian) AI techniques with domain knowledge from industrial partners. Please see this video (https://youtu.be/QYbcm6G_wsk) on Natural Artificial Intelligence for more information about our research.

The Netherlands is in the middle of an energy transition in which the energy network plays a crucial role. The limited capacity of the energy network leads to net congestions that threaten the reliability and expansion of the energy network, with adverse effects on the energy transition and economic growth.

Your main task will be to design artificial agents for flexible energy management, on an individual and collective level, based on a leading physics/neuroscientific theory about computation in the brain, the Free Energy Principle (FEP). You will work closely with industry partners that specialize in energy management solutions, and with Alliander (https://www.alliander.com/en/), a leading developer and maintainer of energy networks in the Netherlands.

This postdoc position is funded by AiNed InnovationLabs (https://ained.nl/en/current-calls/call-ained-innovatielabs-2024-stichting-ained/), which stimulates the development of new AI applications by Dutch industry and public organizations. Therefore, the project has a strong application-driven character. You will work in the BIASlab (http://biaslab.org) team in the Electrical Engineering department at TU/e. This lab focuses its research activities on transferring the FEP to practical use in engineered solutions. During this project you will closely collaborate with other BIASlab researchers, as well as with industry partners and affiliated knowledge institutes.

Key areas of interest include Bayesian machine learning, probabilistic graphical models (factor graphs) and probabilistic programming.

Job Requirements

• Motivated researcher, with a PhD in (Bayesian) machine learning, physics, computer science, or a comparable domain.
• Ability to conduct high quality academic research, reflected in demonstratable outputs.
• A team player who enjoys coaching PhD and Master students, and working in a dynamic, interdisciplinary team.
• A proven ability to manage complex projects to completion on schedule.
• Excellent (written and verbal) proficiency in English, good communication and leadership skills.

Conditions of Employment

A meaningful job in a dynamic and ambitious university, in an interdisciplinary setting and within an international network. You will work on a beautiful, green campus within walking distance of the central train station. In addition, we offer you:

• Full-time employment for 2.5 years.
• Salary in accordance with the Collective Labour Agreement for Dutch Universities, scale 10 (min. € 4,060 max. € 5,331).
• A year-end bonus of 8.3% and annual vacation pay of 8%.
• High-quality training programs on general skills, didactics and topics related to research and valorization.
• An excellent technical infrastructure, on-campus children's day care and sports facilities.
• Partially paid parental leave and an allowance for commuting, working from home and internet costs. 
• A TU/e Postdoc Association that helps you to build a stronger and broader academic and personal network, and offers tailored support, training and workshops.
• A Staff Immigration Team is available for international candidates, as are a tax compensation scheme (the 30% facility) and a compensation for moving expenses.

Information

Do you recognize yourself in this profile and would you like to know more? Visit our website for more information about the application process or the conditions of employment. You can also contact dr. Thijs van de Laar at t.w.v.d.laar@tue.nl for more information about the advertised position.

Are you inspired and would like to know more about working at TU/e? Please visit our career page.

Application

We invite you to submit a complete application using the apply-button. The application should include a:

• Cover letter (max 1 page) in which you describe your motivation and qualifications for the position.
• Curriculum vitae, including a list of your publications and the contact information of three references.
• List of five self-selected ‘best publications’.
• If you have written open-source software code, please provide a download link.

We look forward to receiving your application and will screen it as soon as possible. The vacancy will remain open until the position is filled.