AiBLE Lab 2 PhD Positions

Challenge: Build lasting and liveable environments with and for people.
Change : Embed AI in a multi-actor setting to facilitate the design of the built environment and drive behaviour change.
Impact: Close the policy-practice gap responsibly and inclusively.

TU Delft is a top tier university and is exceedingly active in the field of Artificial intelligence. The AiBLE lab will investigate how AI can be developed and used in complex real-world scenarios to help reach effective, transparent, and lasting design decisions and agreements. In AiBLE we also incorporate human feedback in the loop to iteratively improve decision-making and drive behaviour changes.

AiBLE will focus on two important challenges in the built environment: energy transition and circularity. By using AI to augment human intelligence and support negotiation continuously while adapting to and driving human behaviours, our lab will close the policy-practice gap responsibly and inclusively. We aim also for the acceleration of adoption and acceptance of responsible and inclusive AI.

AiBLE has 4 PhD positions (for position 2 and 3 we have already selected new colleagues), we currently are actively recruiting for position 1 and 4:

Position 1) How can the use of AI in multi-actor settings contribute to a collaborative circular built environment strategy? This project will first analyze and then model multi-actor preferences with regards to the circular transition in the built environment.  This will then inform the design and experimentation of AI technologies in multi-actor real-world settings to examine how design decisions can be made collaboratively to reach more circular outcomes. In this iterative process, it is crucial to combine existing and newly-obtained data from multiple sources with feedback from users to allow continuous improvement.” (Daily supervisor: Dr. Tong Wang, Dr. Luciano Siebert; Promotor: Prof. dr. Paul Chan; Place: Management in the Built Environment, Faculty of Architecture and the Built Environment)

Position 4) Reinforcement learning for human-AI interaction in the built environment. How can AI be used for learning to influence built environment users to make more sustainable choices? This project will explore the potential of AI-based agents such as digital assistants and social robots that are embodied and embedded in the built environment to form an ongoing relationship with users and influence their daily decisions to make more sustainable choices for circularity and energy transition. Techniques from interactive machine learning and reinforcement learning will be developed and applied to the problem of long-term interaction to create agents that can maintain a trustworthy and persuasive relationship with users. (Daily supervisor: Dr. Frank Broz, Dr. Luciano Siebert, Dr. Tong Wang; Promotor: Prof. dr. Catholijn Jonker; Place: Interactive Intelligence Group, Faculty of Electrical Engineering, Mathematics and Computer Science)

For both positions we expect you to have:

• Completed a relevant MSc degree in an applied sciences field relevant to PhD research
• An affinity with teaching and guiding students
• Proficiency in expressing yourself verbally and in writing in English
• The ability to work in a team and take initiative
• Programming skills (Python required and others are a plus)
• Interest in interdisciplinary research

For position 1 we expect you to have:

• Knowledge about circularity in the Architecture, Engineering and Construction sector
• Experience with co-design process;

For position 4 we expect you to have:

• Experience with machine learning and AI techniques for sequential decision making (reinforcement learning, planning under uncertainty, etc)
• Experience designing and evaluating AI systems in interactive contexts (human-robot interaction, spoken dialog systems, etc)

You will receive a 5-year contract and will be deployed for AI-related education for the usual teaching effort for PhD candidates in the faculty plus an additional 20%. The extra year compared to the usual 4-year contract accommodates the 20% additional AI, Data and Digitalisation education related activities. All team members have many opportunities for self-development. You will be a member of the thriving TU Delft AI Lab community that fosters cross-fertilization between talents with different expertise and disciplines.

Delft University of Technology is built on strong foundations. As creators of the world-famous Dutch waterworks and pioneers in biotech, TU Delft is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society. For generations, our engineers have proven to be entrepreneurial problem-solvers, both in business and in a social context. At TU Delft we embrace diversity and aim to be as inclusive as possible (see our Code of Conduct ). Together, we imagine, invent and create solutions using technology to have a positive impact on a global scale.

Challenge. Change. Impact! 

AiBLE is a TU Delft Artificial Intelligence Lab. Artificial Intelligence, Data and Digitalisation are becoming increasingly important when looking for answers to major scientific and societal challenges. In a TU Delft AI Lab, experts in ‘the fundamentals of AI technology’ along with experts in ‘AI challenges’ run a shared lab. As a PhD, you will work with at least two academic members of staff and three other PhD candidates. In total TU Delft will establish 24 TU Delft AI Labs, where 48 Tenure Trackers and 96 PhD candidates will have the opportunity to push the boundaries of science using AI. Each team is driven by research questions which arise from scientific and societal challenges, and contribute to the development and execution of domain specific education. You will receive a 5-year contract and will be deployed for AI-related education for the usual teaching effort for PhD candidates in the faculty plus an additional 20%. The extra year compared to the usual 4-year contract accommodates the 20% additional AI, Data and Digitalisation education related activities. All team members have many opportunities for self-development. You will be a member of the thriving TU Delft AI Lab community that fosters cross-fertilization between talents with different expertise and disciplines.

AiBLE is led by Dr. Tong Wang (Faculty of Architecture and the Built Environment, department of Management in the Built Environment) and Dr. Luciano Siebert (Faculty of Electrical Engineering, Mathematics and Computer Science, Intelligent Systems department)

The Faculty of Architecture and the Built Environment has a leading role in education and research worldwide. The driving force behind the faculty’s success is its robust research profile combined with the energy and creativity of its student body and academic community. It is buzzing with energy from early in the morning until late at night, with four thousand people studying, working, designing, conducting research and acquiring and disseminating knowledge. Our faculty has a strong focus on 'design-oriented research’, which has given it a top position in world rankings.

Staff and students are working to improve the built environment with the help of a broad set of disciplines, including architectural design, urban planning, building technology, social sciences, process management, and geo-information science. The faculty works closely with other faculties, universities, private parties, and the public sector, and has an extensive network in the Netherlands as well as internationally.

Click here to go to the website of the Faculty of Architecture and the Built Environment.

The Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) brings together three disciplines - electrical engineering, mathematics and computer science. Combined, they reinforce each other and are the driving force behind the technology we use in our daily lives. Technology such as the electricity grid, which our faculty is helping to make future-proof. We are also working on a world in which humans and computers reinforce each other. We are mapping out disease processes using single cell data, and using mathematics to simulate gigantic ash plumes after a volcanic eruption. There is plenty of room here for ground-breaking research. We educate innovative engineers and have excellent labs and facilities that underline our strong international position. In total, more than 1,100 employees and 4,000 students work and study in this innovative environment.

Click here to go to the website of the Faculty of Electrical Engineering, Mathematics and Computer Science.

For information about the positions, please contact Dr. Tong Wang ([email protected] )

Are you interested in this vacancy? Please apply no later than June 10, 2022 via the apply button.

For more information about the application procedure, please contact Caro Coemans (HR advisor) via: [email protected].

Please submit the following:

• 1-page Motivation letter
• Your CV
• (part of your) M.Sc. thesis or a paper that you have written, in which you demonstrate your writing (and scientific) skills.
• A position paper (max 2 pages) in which you describe specific points of interest and the approach you would like to take for the PhD position

  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.
• Acquisition in response to this vacancy is not appreciated.

Challenge: Build lasting and liveable environments with and for people.
Change : Embed AI in a multi-actor setting to facilitate the design of the built environment and drive behaviour change.
Impact: Close the policy-practice gap responsibly and inclusively.

TU Delft is a top tier university and is exceedingly active in the field of Artificial intelligence. The AiBLE lab will investigate how AI can be developed and used in complex real-world scenarios to help reach effective, transparent, and lasting design decisions and agreements. In AiBLE we also incorporate human feedback in the loop to iteratively improve decision-making and drive behaviour changes.

AiBLE will focus on two important challenges in the built environment: energy transition and circularity. By using AI to augment human intelligence and support negotiation continuously while adapting to and driving human behaviours, our lab will close the policy-practice gap responsibly and inclusively. We aim also for the acceleration of adoption and acceptance of responsible and inclusive AI.

AiBLE has 4 PhD positions (for position 2 and 3 we have already selected new colleagues), we currently are actively recruiting for position 1 and 4:

Position 1) How can the use of AI in multi-actor settings contribute to a collaborative circular built environment strategy? This project will first analyze and then model multi-actor preferences with regards to the circular transition in the built environment.  This will then inform the design and experimentation of AI technologies in multi-actor real-world settings to examine how design decisions can be made collaboratively to reach more circular outcomes. In this iterative process, it is crucial to combine existing and newly-obtained data from multiple sources with feedback from users to allow continuous improvement.” (Daily supervisor: Dr. Tong Wang, Dr. Luciano Siebert; Promotor: Prof. dr. Paul Chan; Place: Management in the Built Environment, Faculty of Architecture and the Built Environment)

Position 4) Reinforcement learning for human-AI interaction in the built environment. How can AI be used for learning to influence built environment users to make more sustainable choices? This project will explore the potential of AI-based agents such as digital assistants and social robots that are embodied and embedded in the built environment to form an ongoing relationship with users and influence their daily decisions to make more sustainable choices for circularity and energy transition. Techniques from interactive machine learning and reinforcement learning will be developed and applied to the problem of long-term interaction to create agents that can maintain a trustworthy and persuasive relationship with users. (Daily supervisor: Dr. Frank Broz, Dr. Luciano Siebert, Dr. Tong Wang; Promotor: Prof. dr. Catholijn Jonker; Place: Interactive Intelligence Group, Faculty of Electrical Engineering, Mathematics and Computer Science)

For both positions we expect you to have:

• Completed a relevant MSc degree in an applied sciences field relevant to PhD research
• An affinity with teaching and guiding students
• Proficiency in expressing yourself verbally and in writing in English
• The ability to work in a team and take initiative
• Programming skills (Python required and others are a plus)
• Interest in interdisciplinary research

For position 1 we expect you to have:

• Knowledge about circularity in the Architecture, Engineering and Construction sector
• Experience with co-design process;

For position 4 we expect you to have:

• Experience with machine learning and AI techniques for sequential decision making (reinforcement learning, planning under uncertainty, etc)
• Experience designing and evaluating AI systems in interactive contexts (human-robot interaction, spoken dialog systems, etc)

You will receive a 5-year contract and will be deployed for AI-related education for the usual teaching effort for PhD candidates in the faculty plus an additional 20%. The extra year compared to the usual 4-year contract accommodates the 20% additional AI, Data and Digitalisation education related activities. All team members have many opportunities for self-development. You will be a member of the thriving TU Delft AI Lab community that fosters cross-fertilization between talents with different expertise and disciplines.

Delft University of Technology is built on strong foundations. As creators of the world-famous Dutch waterworks and pioneers in biotech, TU Delft is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society. For generations, our engineers have proven to be entrepreneurial problem-solvers, both in business and in a social context. At TU Delft we embrace diversity and aim to be as inclusive as possible (see our Code of Conduct ). Together, we imagine, invent and create solutions using technology to have a positive impact on a global scale.

Challenge. Change. Impact! 

AiBLE is a TU Delft Artificial Intelligence Lab. Artificial Intelligence, Data and Digitalisation are becoming increasingly important when looking for answers to major scientific and societal challenges. In a TU Delft AI Lab, experts in ‘the fundamentals of AI technology’ along with experts in ‘AI challenges’ run a shared lab. As a PhD, you will work with at least two academic members of staff and three other PhD candidates. In total TU Delft will establish 24 TU Delft AI Labs, where 48 Tenure Trackers and 96 PhD candidates will have the opportunity to push the boundaries of science using AI. Each team is driven by research questions which arise from scientific and societal challenges, and contribute to the development and execution of domain specific education. You will receive a 5-year contract and will be deployed for AI-related education for the usual teaching effort for PhD candidates in the faculty plus an additional 20%. The extra year compared to the usual 4-year contract accommodates the 20% additional AI, Data and Digitalisation education related activities. All team members have many opportunities for self-development. You will be a member of the thriving TU Delft AI Lab community that fosters cross-fertilization between talents with different expertise and disciplines.

AiBLE is led by Dr. Tong Wang (Faculty of Architecture and the Built Environment, department of Management in the Built Environment) and Dr. Luciano Siebert (Faculty of Electrical Engineering, Mathematics and Computer Science, Intelligent Systems department)

The Faculty of Architecture and the Built Environment has a leading role in education and research worldwide. The driving force behind the faculty’s success is its robust research profile combined with the energy and creativity of its student body and academic community. It is buzzing with energy from early in the morning until late at night, with four thousand people studying, working, designing, conducting research and acquiring and disseminating knowledge. Our faculty has a strong focus on 'design-oriented research’, which has given it a top position in world rankings.

Staff and students are working to improve the built environment with the help of a broad set of disciplines, including architectural design, urban planning, building technology, social sciences, process management, and geo-information science. The faculty works closely with other faculties, universities, private parties, and the public sector, and has an extensive network in the Netherlands as well as internationally.

Click here to go to the website of the Faculty of Architecture and the Built Environment.

The Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) brings together three disciplines - electrical engineering, mathematics and computer science. Combined, they reinforce each other and are the driving force behind the technology we use in our daily lives. Technology such as the electricity grid, which our faculty is helping to make future-proof. We are also working on a world in which humans and computers reinforce each other. We are mapping out disease processes using single cell data, and using mathematics to simulate gigantic ash plumes after a volcanic eruption. There is plenty of room here for ground-breaking research. We educate innovative engineers and have excellent labs and facilities that underline our strong international position. In total, more than 1,100 employees and 4,000 students work and study in this innovative environment.

Click here to go to the website of the Faculty of Electrical Engineering, Mathematics and Computer Science.

For information about the positions, please contact Dr. Tong Wang ([email protected] )

Are you interested in this vacancy? Please apply no later than June 10, 2022 via the apply button.

For more information about the application procedure, please contact Caro Coemans (HR advisor) via: [email protected].

Please submit the following:

• 1-page Motivation letter
• Your CV
• (part of your) M.Sc. thesis or a paper that you have written, in which you demonstrate your writing (and scientific) skills.
• A position paper (max 2 pages) in which you describe specific points of interest and the approach you would like to take for the PhD position

  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.
• Acquisition in response to this vacancy is not appreciated.