PhD position: Energy transition in the built environment: economic behavior, social networks and artificial intelligence.
Department of the Built Environment
Architecture, Building and Planning
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, this involves more than 5 million dwellings and many billions euros in costs. A considerable part of these costs has to be carried by house owners, and the challenge is to motivate them to timely invest in energy retrofitting. This project studies how artificial intelligence driven online platforms can stimulate and support energy transition of individual house owners and whole neighborhoods, and help people 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 Dutch municipalities and online platform providers. Your research will generate novel big-data-driven scientific insights into the effectiveness of smart technologies and AI in changing people’s energy-saving behavior. First, using big data over past years and statistical/data science methods, you will evaluate how existing online platforms affected energy investment behavior of house owners and try to figure out best practices. Special attention will be paid to the role of social networks and collective decision-making (e.g. in the neighborhood). Second, based on theories of individual and collective economic behavior, you will develop and run real life experiments to improve the effectiveness of the platforms.
This position is part of a large transdisciplinary grant “Energy Transition in the Built Environment”.
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.
We are looking for high-level candidates with an MSc degree in engineering, exact/life sciences, quantitative economics/econometrics, data science or equivalent. She or he should be interested in (i) energy transition, (ii) understanding and modelling human economic behavior and the impact of social networks and smart technology on it, and (iii) computational modelling, artificial intelligence and work with big data.
The candidates should have:
• An MSc degree in engineering, exact/life sciences, quantitative economics/econometrics or equivalent.
• A strong education track-record that includes topics such as calculus, computational modelling, data science, or equivalent.
• Strong demonstrable analytical skills.
• A proven ability to write computer code and to organise data.
• Strong communication skills, including proficiency in English (spoken and written).
• Affinity for working in an interdisciplinary and highly international environment.
Conditions of employment
Conditions of employment
• 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/
Information and application
Information and application
If you have questions about the content of this positon, 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:
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.
You can upload a maximum of 5 documents of up to 10 MB each. Please upload (in pdf format):
• A letter of motivation (max. 2 pages),
• Curriculum vitae,
• Copy (or a most recent draft version) of your MSc thesis,
• Transcripts of academic records indicating courses taken, including grades,
• Contact details of two references (e-mail, phone number).
Closing date is 20 February 2020, but the applications will be considered as they come in.
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