TU Delft is a top tier university and is exceedingly active in the field of Artificial intelligence. The XAIT (eXplainable AI Twins for Resilient Cities) lab aims to develop novel approaches that focus on the explainable aspect of artificial intelligence. The goal is to develop methods that not only exhibit excellent performance, but also concisely break down the main factors behind automated decision-making in a way that is easy for humans to interpret.

Our aim is to augment digital twins (digital replicas) of cities with this technology, creating a new class of AI twins for cities. Such approaches provide tangible and concrete decision support to enable resilient cities to tackle urban problems such as evacuation, energy, long-term planning, and infrastructure operations.

XAIT Lab has 4 PhD positions:

(1) XAI for unravelling multimodal interactions - Develop explainable AI to analyse large-scale data to understand the complex dynamics of multimodal transportation and their interaction with exogenous conditions such as land use, weather and air quality.

(2) XAI for predictions under exceptional conditions - Incorporate explainability in reinforcement learning techniques for predictions under rare/exceptional events such as evacuation scenarios, loss of structural integrity and high-density crowding.

(3) XAI for large-scale optimisation - Enhance combinatorial optimisation algorithms with transparency, e.g., by providing human-understandable certificates to convince the human that the solution is indeed the best possible solution. 

(4) XAI for sustainable anticipatory traffic management - Develop explainable algorithms to solve problems where the integration of (multi-objective) combinatorial optimisation and machine learning is essential such as handling evacuation events and contingency planning for disasters.

XAIT Lab is led by Panchamy Krishnakumari (Faculty of Civil Engineering and Geosciences + Department of Transport and Planning) and Emir Demirović (Faculty of Engineering, Mathematics and Computer Science + Department of Software and Computer Technology). 

For all 4 positions we expect you to have:

• Completed a relevant MSc degree in a relevant field, i.e. Computer Science, Transportation, Information Communication and Technology, Mathematics or an Applied Science field;
  
• Knowledge in programming, e.g., Python, C/C++;
• An affinity for software engineering skills;
• 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.

Furthermore, for position 1 we expect you to have:

• Knowledge in (big) data science;
• Affinity for feature engineering, network science and/or multimodal mobility.

For position 2, we expect you to have:

• Knowledge in machine learning;
• Affinity for reinforcement learning and/or machine learning fundamentals.

For position 3, we expect you to have:

• Knowledge in combinatorial optimisation, e.g., SAT solving, constraint programming, integer programming;
• Programming skills, preferably C/C++;
• Knowledge of complex data structures.

For position 4, we expect you to have:

• Knowledge in mathematical modelling and optimization;
• Knowledge in complex data structures;
• Affinity and understanding for game theory and game-theoretical interactions in complex systems.

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

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! 

XAIT Lab

XAIT Lab 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.

The Faculty of Civil Engineering & Geosciences (CEG) is committed to outstanding international research and education in the field of civil engineering, applied earth sciences, traffic and transport, water technology, and delta technology. Our research feeds into our educational programmes and covers societal challenges such as climate change, energy transition, resource depletion, urbanisation and the availability of clean water, conducted  in close cooperation with a wide range of research institutions. CEG is convinced that Open Science helps to achieve our goals and supports its scientists in integrating Open Science in their research practice. The Faculty of CEG comprises 28 research groups in the following seven departments: Materials Mechanics Management & Design, Engineering Structures, Geoscience and Engineering, Geoscience and Remote Sensing, Transport & Planning, Hydraulic Engineering and Water Management.

Click here to go to the website of the Faculty of Civil Engineering & Geosciences.

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.