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  3. PhD Digital tools to predict & affect clean energy choices of low income familie

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PhD Digital tools to predict & affect clean energy choices of low income familie

Eindhoven University of Technology is looking for a PhD candidate with a background in Exact or data sciences/ (Industrial) Engineering/ Quantitative economics, interested in developing digital and artificial intelligence-based tools to predict and affect clean energy choices of low-income families.

ongeveer een maand geleden


de Rondom, Eindhoven, Noord-Brabant
Tijdelijk contract / Tijdelijke opdracht
Uren per week:
38 uur


Job description


In the coming decades, many countries need to improve the energy efficiency of their building stock, to realize the climate and renewable energy goals. In the Netherlands, some 2 million social housing dwellings will undergo a radical upgrade in the way homes are insulated and heated. This transition may have an important side effect: help alleviate energy poverty for low-income families who now have difficulty paying their energy bills. This project studies how digital and artificial intelligence-based tools can stimulate and support energy transition of low-income families and help them make optimal technology choices.

We are looking for a PhD-candidate to join a team of researchers and practitioners, in which TU Eindhoven collaborates with behavioural economists, data scientists as well as public housing providers. Your research will first generate novel big-data-based evidence on the returns and behavioural effects of energy efficiency investments in public housing, and the corresponding energy poverty relief. Then, the results will enter as input into a digital tool that allows to predict and affect clean energy behaviour of low-income families in different scenarios.

This position is part of a large transdisciplinary grant 'Behaviour, Energy transition, Low income'

The team

You will join the Urban Systems and Real Estate Group of the Department of the Built Environment of Eindhoven University of Technology (TU/e). TU/e is a world-leading research university specializing in engineering science & technology, and is the world's best-performing university in terms of cooperation between research and industry (#1 since 2009). The Department of the Built Environment is responsible for research and education in Architecture, Civil Engineering, Urban Planning, Urban Economics and Real Estate. The department has a strong focus on the highly socially relevant fields of smart cities and sustainable systems.

The Urban Systems and Real Estate group consists of three full professors, ten assistant and associate professors, several postdocs, about 40 PhD and PDEng candidates and support staff. The USRE group is world-renowned for its research on mobility, urban planning, urban economics, real estate and information systems in the built environment. The group has a strong focus on the analysis and modelling of individuals' behavior and use of smart technologies to create more sustainable solutions and healthy environments for people.

The PhD program (https://www.tue.nl/en/education/graduate-school/phds-at-tue/ )

PhD programs at TU/e are four-year research positions, having as aim to educate excellent, independent researchers. The program is in English and entails: (i) post-master level education in the form of courses and projects, (ii) performing cutting-edge research that results in scientific publications and concrete practical applications. TU/e with its nine departments offers a wide choice of educational and scientific activities covering various subjects. Within the research group personal scientific development is supported among other things by biweekly scientific seminars as well as participation in yearly international conferences in different countries.


The candidates should have:

∙An MSc degree in Exact or data sciences/ (Industrial) Engineering/ Quantitative economics/ Computer sciences, statistics and mathematics.

∙A strong educational track-record including at least several of the following subjects: calculus, linear algebra, computational modelling, microeconomics, econometrics, operations research, data science.

∙A proven experience with programming (preferably in Python) and working with (big) data.

∙Having working experience at a European research institute or a European university is an advantage.

∙Strong demonstrable analytical skills and proficiency in English (spoken and written).

∙Affinity with collaboration with industry, ability to bring together fundamental and applied research.


Conditions of employment

We offer:

• A challenging job at a dynamic and ambitious university, in collaboration with experienced scientists and hi-tech companies.

• Support to your personal development and career planning.

• A full-time employment for 4 years. Gross monthly salaries are in accordance with the Collective Labour Agreement of the Dutch Universities (CAO NU), increasing from € 2325 per month initially, to € 2972 in the fourth year.

• An attractive package of fringe benefits including excellent work facilities, end of the year allowance, etc. The university provides all general modern facilities belonging to first class universities: mediation in housing, excellent sports facilities, language courses, modern digital library etc.

• See also www.tue.nl/en/working-at-tue/why-tue/compensation-and-benefits/

Additional information

Information and application


If you have questions about the content of this position, please contact:

• Dr. Ioulia Ossokina, assistant professor Housing research and modelling: i.v.ossokina[at]tue.nl, www.ossokina.com

• Prof. dr. Theo A. Arentze, professor of Real Estate Management and Development: t.a.arentze[at]tue.nl, www.tue.nl/en/research/researchers/theo-arentze/

Information about the employment conditions can be found here: https://www.tue.nl/en/careers/working-conditions/


You can respond to this vacancy via our application page www.tue.nl/jobs by clicking on the button "Solliciteer op deze vacature / Apply for this job". We do not respond to applications that are sent to us in a different way.

Please upload (in pdf format):

∙ Cover letter (2 page max), which includes a motivation of your interest and an explanation of why you meet the job requirements (see above).

∙ Detailed Curriculum vitae,

∙ Copy (or a most recent draft version) of your MSc thesis,

∙ Transcripts of academic records (bachelor and master) indicating courses taken, including grades,

∙ Contact details of two references (e-mail, phone number).

Closing date is 1 June 2020, but the applications will be considered as they come in.

You can only upload a maximum of 1 document of 10 Mb.