Publisher
source

Wageningen University & Research

PhD in Decision-Making for Heat Transition Planning under Data Sharing Constraints Wageningen University & Research in Netherlands

Degree Level

PhD

Field of study

Computer Science

Funding

Fully funded PhD position with a tailored course program. Gross salary starts at €3,059 per month in year 1 and rises to €3,881 per month in year 4, based on a 38-hour work week. Temporary contract for 18 months, extendable for the project duration if performance is good.

Deadline

Sep 14, 2026

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Country

Netherlands

University

Wageningen University & Research

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Keywords

Computer Science
Data Science
Machine Learning
Environmental Science
Electrical Engineering
Mathematics
Decision Making
Industrial Engineering
Python Programming
Uncertainty Analysis
Optimisation
Statistics
Renewable Energy Systems

About this position

PhD opportunity at Wageningen University & Research in Decision-Making for Heat Transition Planning under Data Sharing Constraints.

This project sits in the Information Technology Group at Wageningen University and is part of the newly funded NWO KIC project “Sharing the Warmth”, an interdisciplinary collaboration with TU Delft, Hogeschool Utrecht, CWI, Dutch municipalities, DSOs, and other societal and industry partners.

The research focuses on energy systems, electricity distribution systems, heat transition planning, optimization, machine learning, uncertainty quantification, and distributed decision-making. The core challenge is how grid operators, municipalities, and other stakeholders can make robust planning and operational decisions when the data they need are incomplete, decentralized, privacy-sensitive, or otherwise difficult to share. Flexible electrification technologies, especially heat pumps, are the main use case.

You will investigate data requirements, governance and privacy barriers, and methods for robust decision-making under realistic data-sharing constraints. Possible approaches include mathematical modelling, machine learning, uncertainty-aware methods, and data-driven optimization. The project offers access to real-world datasets and case studies through municipalities, DSOs, and industrial partners, and includes collaboration with other PhD candidates and a postdoctoral researcher on related topics such as energy data spaces, privacy-preserving data sharing, governance, and citizen participation.

Eligibility highlights: an MSc in a relevant field such as electrical engineering, energy systems, computer science, applied mathematics, artificial intelligence, or data science; strong interest in future energy systems; desirable experience in modelling, optimization, ML, or data analytics; strong Python programming skills; and English at C1 level with an internationally recognized proficiency certificate.

Funding: fully funded PhD position with a salary according to Dutch university scales (€3,059/month in year 1 up to €3,881/month in year 4), plus a tailored course program and employment benefits. The contract is initially for 18 months and may be extended for the full project duration.

Location: Wageningen, Netherlands.

Deadline: apply by 2026-09-14. Interviews are scheduled for September–October 2026. Start date is intended for November 2026.

How to apply: submit your application through the WUR vacancy page only. Upload a CV, motivation letter, and bachelor transcript, and complete the mandatory Microsoft form linked in the post.

Funding details

Fully funded PhD position with a tailored course program. Gross salary starts at €3,059 per month in year 1 and rises to €3,881 per month in year 4, based on a 38-hour work week. Temporary contract for 18 months, extendable for the project duration if performance is good.

What's required

Applicants must have a successfully completed MSc degree in a relevant discipline such as electrical engineering, energy systems, computer science, applied mathematics, artificial intelligence, or data science. Strong interest in novel decision-making methods for future energy systems, especially electricity distribution systems, energy system planning, and flexible energy resources such as heat pumps, is required. Knowledge of mathematical modelling, optimization, machine learning, or data analytics is desirable. Strong scientific programming skills in Python are expected, and excellent English communication skills are required at C1 level with an internationally recognized Certificate of Proficiency in English.

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