PhD Positions on Computer Vision and Deep Learning for Architectural Design

Updated: 13 days ago
Deadline: 30 Nov 2021

Challenge: Developing data-driven solutions for automatic perception and understanding of visual data in architectural design.
Change: Competent solutions for design challenges in Architecture and built environment.

Faculty of Architecture and the Built Environment at TU Delft is a pioneering world-class university (ranked second in the QS academic ranking at 2020), both in research and education. The newly established AiDAPT lab (Ai for Design, Analysis, and OPTimization) at the Department of Architecture is an interdisciplinary research group investigating state-of-the-art computer vision methods in architectural design, i.e., data-driven artificial intelligence for visual perception and understanding. The emphases are on external validation of AI disciplinary approaches by using real data from the domain of Architecture. We are seeking a PhD candidate who is highly motivated to work at the computer vision and architecture confluence.

A fair part of our planet is considered as “built environment”. There is a large amount of digital footprint and visual data such as street-view images, maps and interior photos, floor plans, etc. Efficient exploration and analysis of these available data require intelligent tools. Therefore the result is a greater understanding and a superior design of our living environment by architects, designers, and engineers to solve real-world challenges such as sustainability, or health. The Lab’s research agenda focuses on state-of-the-art artificial intelligence methods for automatic recognition and understanding of visual attributes in architectural data: from images of built-forms, to architectural representations and design models. The challenges are the

  • Positioning and analysing the state of Computer vision discipline with respect to the demands for efficient and novel computational frameworks in the domain of Architectural design.
  • Data efficiency in the context of unsupervised methods for inductive biases such as shapes and image formats in architectural visual forms and data.
  • Data collection in the context of the data-hungry supervised-learning models for the visual understanding of the built\design representations.
  • Subjectivity in the human-level supervision, e.g., disagreement in the data annotation due to the complex or multifaceted perception of the architectural objects and concepts.
  • Communication of the research outcomes to the domain experts (non-computer scientists) particularly in the lack of explainability in the modern machine-learning models.

AiDAPT lab at Architecture offers a Ph.D. position to address the challenges of computer vision for built/design-form recognition and understanding. Your role is to study, analyze and develop deep learning neural network models and the benchmark datasets for visual learning in architectural data. To train and evaluate competent computer vision models, you will work with convolutional neural networks and deep learning programming frameworks such as PyTorch and TensorFlow.

Research Group:
The AiDAPT lab is led by Seyran Khademi (Department of Architecture) and Charalampos Andriotis (Department of Architectural Engineering and Technology) at the Faculty of Architecture and the Built Environment at TU Delft. You will work at the Department of Architecture and in close collaboration with the Computer Vision lab at the faculty of Computer Science.  You’ll be part of the Theory of Architecture and Digital Culture Group that studies the evolving relationship between AI and architecture discipline.

  • MSc degree (or can be expected in the coming months) in Architectural design with a computational background, Computer science, Applied mathematics, or in a related discipline.
  • A proven record (e.g., GitHub, Kaggle profiles) in Programming (Python, PyTorch, TensorFlow, CUDA or similar), Machine-learning and Data Analytics.
  • A proven interest in interdisciplinary research such as publications, thesis or software at the intersection of the two domains of Architecture and Computer science.
  • Excellent communication skills in English, both in written and oral.
  • An affinity to teaching and supervision of the students.
  • The ability to work independently as a researcher and initiate a collaboration with fellow academics.

TU Delft offers DAI-Lab PhD candidates a 5-year contract (as opposed to the normal 4-years), with an official go/no go progress assessment after one year. Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from € 2395 per month in the first year to € 3217 in the fifth 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 research skills. The TU Delft offers a customizable compensation package, discounts on health insurance and sport memberships, and a monthly work cost contribution. For international applicants, we offer the Coming to Delft Service and Partner Career Advice to assist you with your relocation.    

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. For generations, our engineers have proven to be entrepreneurial problem-solvers both in business and in a social context. TU Delft offers 16 Bachelor’s and 32 Master’s programmes to more than 23,000 students. Our scientific staff consists of 3,500 staff members and 2,800 PhD candidates. Together we imagine, invent and create solutions using technology to have a positive impact on a global scale.

Challenge. Change. Impact!

AiDAPT Lab is a 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 DAI-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 DAI-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 students 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 DAI-Lab community that fosters cross-fertilization between talents with different expertise and disciplines.

The AiDAPT lab is led by Seyran Khademi and Charalampos Andriotis at the intersection of the two departments of Architecture and Architectural Engineering and Technology at the faculty of Architecture and the Built environment at TUDelft. You will work at the Department of Architecture and in close collaboration with the Computer Vision lab at the faculty of Computer Science.  You’ll be part of the research group of Theory of Architecture and Digital Culture that studies the evolving relationship between AI and architecture discipline. This is an interdisciplinary research and education environment which aims at building a bridge between the Computer Science and Architecture departments at the university level.

For information about this vacancy, you can contact Seyran Khademi, Assistant Professor, email: s.khademi@tudelft.nl.

For information about the selection procedure, please contact Caro Coemans, HR advisor, email: HR-BK@tudelft.nl

Please submit your application online no later than November 30, 2021 (Local Dutch time: UTC-time + 2 hrs). You can only apply via the application button 'Apply now'; applications sent to one of the mentioned email addresses will not be processed. 

You can only apply via the application button 'Apply now'; applications sent to one of the mentioned email addresses will not be processed.

To apply, please prepare:

  • A detailed CV including your education, work experiences, completed or ongoing projects, e.g., in GitHub repository or other public platforms, publications and achievements that demonstrate your relevant competencies.
  • A proof of experiences (e.g., transcript of records) in subjects such as computer vision, machine/deep learning, linear algebra, calculus, statistics, signal and image processing and random processes.
  • A 1-page motivation letter addressing your interests and describing how your experience and plans fit the advertised position.
  • Two references contact information (Not recommendation letters).
  • MSc thesis or any publications you have authored (a URL to a PDF is also acceptable).

All documents should be in PDF format with a file named: lastname_firstname_docname.zip.

We would like to arrange interviews for selected candidates in late October 2021. The tentative starting date for this position is January 2022. 

Please note that incomplete applications will not be processed.


Challenge: Developing data-driven solutions for automatic perception and understanding of visual data in architectural design.
Change: Competent solutions for design challenges in Architecture and built environment.

Faculty of Architecture and the Built Environment at TU Delft is a pioneering world-class university (ranked second in the QS academic ranking at 2020), both in research and education. The newly established AiDAPT lab (Ai for Design, Analysis, and OPTimization) at the Department of Architecture is an interdisciplinary research group investigating state-of-the-art computer vision methods in architectural design, i.e., data-driven artificial intelligence for visual perception and understanding. The emphases are on external validation of AI disciplinary approaches by using real data from the domain of Architecture. We are seeking a PhD candidate who is highly motivated to work at the computer vision and architecture confluence.

A fair part of our planet is considered as “built environment”. There is a large amount of digital footprint and visual data such as street-view images, maps and interior photos, floor plans, etc. Efficient exploration and analysis of these available data require intelligent tools. Therefore the result is a greater understanding and a superior design of our living environment by architects, designers, and engineers to solve real-world challenges such as sustainability, or health. The Lab’s research agenda focuses on state-of-the-art artificial intelligence methods for automatic recognition and understanding of visual attributes in architectural data: from images of built-forms, to architectural representations and design models. The challenges are the

  • Positioning and analysing the state of Computer vision discipline with respect to the demands for efficient and novel computational frameworks in the domain of Architectural design.
  • Data efficiency in the context of unsupervised methods for inductive biases such as shapes and image formats in architectural visual forms and data.
  • Data collection in the context of the data-hungry supervised-learning models for the visual understanding of the built\design representations.
  • Subjectivity in the human-level supervision, e.g., disagreement in the data annotation due to the complex or multifaceted perception of the architectural objects and concepts.
  • Communication of the research outcomes to the domain experts (non-computer scientists) particularly in the lack of explainability in the modern machine-learning models.

AiDAPT lab at Architecture offers a Ph.D. position to address the challenges of computer vision for built/design-form recognition and understanding. Your role is to study, analyze and develop deep learning neural network models and the benchmark datasets for visual learning in architectural data. To train and evaluate competent computer vision models, you will work with convolutional neural networks and deep learning programming frameworks such as PyTorch and TensorFlow.

Research Group:
The AiDAPT lab is led by Seyran Khademi (Department of Architecture) and Charalampos Andriotis (Department of Architectural Engineering and Technology) at the Faculty of Architecture and the Built Environment at TU Delft. You will work at the Department of Architecture and in close collaboration with the Computer Vision lab at the faculty of Computer Science.  You’ll be part of the Theory of Architecture and Digital Culture Group that studies the evolving relationship between AI and architecture discipline.

  • MSc degree (or can be expected in the coming months) in Architectural design with a computational background, Computer science, Applied mathematics, or in a related discipline.
  • A proven record (e.g., GitHub, Kaggle profiles) in Programming (Python, PyTorch, TensorFlow, CUDA or similar), Machine-learning and Data Analytics.
  • A proven interest in interdisciplinary research such as publications, thesis or software at the intersection of the two domains of Architecture and Computer science.
  • Excellent communication skills in English, both in written and oral.
  • An affinity to teaching and supervision of the students.
  • The ability to work independently as a researcher and initiate a collaboration with fellow academics.

TU Delft offers DAI-Lab PhD candidates a 5-year contract (as opposed to the normal 4-years), with an official go/no go progress assessment after one year. Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from € 2395 per month in the first year to € 3217 in the fifth 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 research skills. The TU Delft offers a customizable compensation package, discounts on health insurance and sport memberships, and a monthly work cost contribution. For international applicants, we offer the Coming to Delft Service and Partner Career Advice to assist you with your relocation.    

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. For generations, our engineers have proven to be entrepreneurial problem-solvers both in business and in a social context. TU Delft offers 16 Bachelor’s and 32 Master’s programmes to more than 23,000 students. Our scientific staff consists of 3,500 staff members and 2,800 PhD candidates. Together we imagine, invent and create solutions using technology to have a positive impact on a global scale.

Challenge. Change. Impact!

AiDAPT Lab is a 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 DAI-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 DAI-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 students 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 DAI-Lab community that fosters cross-fertilization between talents with different expertise and disciplines.

The AiDAPT lab is led by Seyran Khademi and Charalampos Andriotis at the intersection of the two departments of Architecture and Architectural Engineering and Technology at the faculty of Architecture and the Built environment at TUDelft. You will work at the Department of Architecture and in close collaboration with the Computer Vision lab at the faculty of Computer Science.  You’ll be part of the research group of Theory of Architecture and Digital Culture that studies the evolving relationship between AI and architecture discipline. This is an interdisciplinary research and education environment which aims at building a bridge between the Computer Science and Architecture departments at the university level.

For information about this vacancy, you can contact Seyran Khademi, Assistant Professor, email: s.khademi@tudelft.nl.

For information about the selection procedure, please contact Caro Coemans, HR advisor, email: HR-BK@tudelft.nl

Please submit your application online no later than November 30, 2021 (Local Dutch time: UTC-time + 2 hrs). You can only apply via the application button 'Apply now'; applications sent to one of the mentioned email addresses will not be processed. 

You can only apply via the application button 'Apply now'; applications sent to one of the mentioned email addresses will not be processed.

To apply, please prepare:

  • A detailed CV including your education, work experiences, completed or ongoing projects, e.g., in GitHub repository or other public platforms, publications and achievements that demonstrate your relevant competencies.
  • A proof of experiences (e.g., transcript of records) in subjects such as computer vision, machine/deep learning, linear algebra, calculus, statistics, signal and image processing and random processes.
  • A 1-page motivation letter addressing your interests and describing how your experience and plans fit the advertised position.
  • Two references contact information (Not recommendation letters).
  • MSc thesis or any publications you have authored (a URL to a PDF is also acceptable).

All documents should be in PDF format with a file named: lastname_firstname_docname.zip.

We would like to arrange interviews for selected candidates in late October 2021. The tentative starting date for this position is January 2022. 

Please note that incomplete applications will not be processed.


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