PhD on Data Integration and Typology-Based BES Modelling for Positive Energy Districts

@Eindhoven University of Technology posted 4 days ago

Job Description

We are seeking a motivated PhD researcher to contribute to the development of scalable and efficient methods for building energy modelling to support Positive Energy Districts (PEDs).

In this position, you will develop a systematic, data-driven approach to identify and model representative building typologies based on public datasets such as BAG, 3DBAG, CBS, satellite imagery, and OpenStreetMap. Your work will focus on enabling the efficient generation of building energy models (BES) at the neighborhood scale, using clustering and sensitivity analysis to reduce model complexity without compromising accuracy. You will also contribute to the development of automated workflows for model creation.

This PhD is part of the EmPowerED research project, which brings together researchers, municipalities, grid operators, housing associations, and citizens to support the design of sustainable, affordable, and widely supported local energy systems. EmPowerED aims to accelerate the energy transition by placing citizens at the heart of PED development through new socio-technical models and tools. You will collaborate closely with a second EmPowerED PhD, who focuses on aligning model complexity with the specific needs of use cases defined by project stakeholders.

You will be embedded in the Building Performance research group and the Information Systems in the Built Environment research group, working in a collaborative and interdisciplinary environment. Your contributions will support municipalities and practitioners in making informed decisions about building performance, energy use, and renovation planning.

We welcome applicants from diverse backgrounds who are enthusiastic about working at the interface of building engineering, data analysis, and building energy modelling.

Job Requirements

  • A master’s degree (or an equivalent university degree) in environmental engineering, building engineering, building physics or data science with strong skills in Python, GIS, and machine learning.
  • A research-oriented attitude.
  • Ability to work in an interdisciplinary team and interested in collaborating with industrial partners.
  • Motivated to develop your teaching skills and coach students.
  • Fluent in spoken and written English (C1 level).

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 four years, with an intermediate assessment after nine months. You will spend a minimum of 10% of your four-year employment on teaching tasks, with a maximum of 15% per year of your employment.
  • Salary and benefits (such as a pension scheme, paid pregnancy and maternity leave, partially paid parental leave) in accordance with the Collective Labour Agreement for Dutch Universities, scale P (min. € 2,901 max. € 3,707).
  • A year-end bonus of 8.3% and annual vacation pay of 8%.
  • High-quality training programs and other support to grow into a self-aware, autonomous scientific researcher. At TU/e we challenge you to take charge of your own learning process.
  • An excellent technical infrastructure, on-campus children’s day care and sports facilities.
  • An allowance for commuting, working from home and internet costs.
  • Staff Immigration Team and a tax compensation scheme (the 30% facility) for international candidates.

Information

Do you recognize yourself in this profile and would you like to know more? Please contact the hiring manager dr.ir. P. Hoes (p.hoes@tue.nl)

Visit our website for more information about the application process or the conditions of employment. You can also contact HR Services (HRservices.be@tue.nl).

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 by using the apply button. The application should include a:

  • Cover letter 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.

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.

Reference number: 2025/303

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