PhD Position in AI for Building Energy Retrofit Planning

  • Contract
  • Anywhere

Delft University of Technology (TU Delft)


13 Jun 2023
Job Information

Organisation/Company
Delft University of Technology (TU Delft)
Research Field
Technology
Researcher Profile
First Stage Researcher (R1)
Country
Netherlands
Application Deadline
2 Jul 2023 – 21:59 (UTC)
Type of Contract
Temporary
Job Status
Not Applicable
Is the job funded through the EU Research Framework Programme?
Not funded by an EU programme
Is the Job related to staff position within a Research Infrastructure?
No

Offer Description

AiDAPT Lab, TU Delft’s Artificial Intelligence Lab for Design, Analysis, and Optimization in Architecture & Built Environment, invites applications for one PhD position in the area of AI for building energy retrofit planning, decision-making, and optimization.

We are looking for candidates highly motivated to work at the confluence of AI, building physics, and energy simulation, in order to address the energy transition needs of our aging and growing building stocks. Recent advances in AI provide us with unprecedented capabilities to scale up and automate our information processing and intervention strategies in complex large-scale settings. In this direction, of particular interest to this research is how we can harness these advances in AI and integrate them with physics-based simulators to make informed building energy retrofit decisions under uncertainty.

The successful candidate will work on the development of a novel data-driven computational framework enabling us to optimize the necessary building interventions at scale, with emphasis on cities in the Netherlands and Rotterdam in particular. This research will produce new AI disciplinary methods that advance our capabilities to streamline retrofit resources for real-world buildings. The research will couple building energy simulation with machine learning methods ranging from deep learning and machine vision to optimization and reinforcement learning, in order to allow for (i) automatic identification of energy-related building characteristics from imagery and other data, (ii) classification of buildings to certain typologies and respective retrofit package options; (iii) probabilistic energy performance assessment and prediction, including future scenarios arising from climate-change; (iv) decision-making regarding the optimal type, time, and place of retrofit solutions.

This research is linked to two TU Delft projects, DE-CIST and MultiCaRe. DE-CIST is a project funded by a granting scheme conducted by Google to foster data-driven environmental and climate action at the local level. The project’s goal is to develop scalable, transferable, and automated data-driven methods, able to bolster energy transition through optimal retrofit planning in the city of Rotterdam. MultiCaRe is a large multi-national project funded by the European Commission and is aimed at creating a novel framework for future-proof façade technologies in the presence of multiple hazards, including seismic and climate-change hazards, by combining energy performance assessment, structural risk quantification, and multi-criteria optimization.

As part of AiDAPT Lab, the successful candidate will hold a joint appointment at the Chair of Structural Design & Mechanics and the Chair of Design, Data and Society, in the Faculty of Architecture & Built Environment, and will be supervised by Dr. Andriotis and Dr. Khademi. (S)he will further work as part of a team closely collaborating with researchers and research groups associated with DE-CIST and MultiCaRe. The position is funded for a duration of 4 years, during which the appointed candidate will (i) undertake research on their PhD topics and (ii) assist with the educational and research agenda of AiDAPT and the host Chairs.

Requirements
Specific Requirements

  • MSc in Architectural Engineering, Civil Engineering or alternatively Computer/Data Science, AI or related fields;
  • Strong background in at least two of building technology (also known as architectural engineering), façade engineering, building physics;
  • Experience with data-driven and deep learning approaches;
  • Interest in the application of deep learning in building energy performance;
  • Excellent programming skills with Python;
  • Familiarity with deep learning frameworks such as Pytorch, and Tensorflow;
  • Excellent oral and written communication skills in English proven by a minimum score of 100 in TOEFL or IELTS of 7.0 per sub-skill (writing, reading, listening, speaking). For more details please check the Graduate Schools Admission Requirements .
  • Teaching interest and/or experience in AI- and structural/architectural design courses.
  • Ability to work in a team, take initiatives, and be results-oriented.

Doing a PhD at TU Delft requires English proficiency at a certain level to ensure that the candidate is able to communicate and interact well, participate in English-taught Doctoral Education courses, and write scientific articles and a final thesis. For more details please check the Graduate Schools Admission Requirements.

Additional Information
Benefits

Doctoral candidates will be offered a 4-year period of employment in principle, but in the form of 2 employment contracts. An initial 1,5 year contract with an official go/no go progress assessment within 15 months. Followed by an additional contract for the remaining 2,5 years assuming everything goes well and performance requirements are met.

Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from € 2541 per month in the first year to € 3247 in the fourth year. As a PhD candidate you will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment with an excellent team of supervisors, academic staff and a mentor. The Doctoral Education Programme is aimed at developing your transferable, discipline-related and research skills.

The TU Delft offers a customisable compensation package, discounts on health insurance and sport memberships, and a monthly work costs contribution. Flexible work schedules can be arranged.

For international applicants, TU Delft has the Coming to Delft Service . This service provides information for new international employees to help you prepare the relocation and to settle in the Netherlands. The Coming to Delft Service offers a Dual Career Programme for partners and they organise events to expand your (social) network.

Selection process

Are you interested in this vacancy? Please apply before 2 July 2023 via the application button and upload:

  • Detailed CV – highlight examples of projects and/or achievements that demonstrate skills relevant to the advertised position;
  • Motivation letter (no more than 600 words) addressing your interests and describing how your experience and plans fit with the position;
  • Contact information for two references (letters not required at this stage);
  • MSc thesis and, if applicable, one or two notable publications you have authored;
  • Undergraduate and graduate transcripts.

Please note:

  • You can apply online. We will not process applications sent by email and/or post.
  • A pre-Employment screening can be part of the selection procedure.
  • Please do not contact us for unsolicited services.

Additional comments

For additional information about the positions please contact Dr. Charalampos Andriotis or Dr. Seyran Khademi at [email protected] ; [email protected] .

The position will remain open until July 2nd, 2023. Applicants are encouraged to apply as soon as possible, because screening of applications and interviews with candidates will begin before the deadline.

Website for additional job details
https://www.academictransfer.com/329024/

Work Location(s)

Number of offers available
1
Company/Institute
Delft University of Technology
Country
Netherlands
City
Delft
Postal Code
2628 CD
Street
Mekelweg 2

Where to apply

Website
https://www.academictransfer.com/329024/phd-position-in-ai-for-building-energy-…

Contact

City
Delft
Website
http://www.tudelft.nl/
Street
Mekelweg 2
Postal Code
2628 CD

STATUS: EXPIRED

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