Challenge:Improve flight efficiency and safety.
Change:Utilize explainable AI (XAI) techniques.
Impact:Contribute to sustainable aviation.
Job descriptionPressing economic, capacity, and environmental concerns are forcing a fundamental redesign of the Air Traffic Management (ATM) system that currently relies heavily on an expert and skilled human workforce. Given that Artificial Intelligence (AI) is expected to transform every aspect of modern society, the ATM community is also considering the introduction of AI-based systems to cope with more stringent safety, environmental and economic constraints. Here, AI is expected to have most impact on long-term, strategic flight planning by providing solutions to both existing (e.g., using historical data) and new (e.g., using reinforcement learning) problems. However, given that AI also needs to satisfy requirements related to reliability, output predictability and ethics, human involvement and supervision remain of paramount important for decades to come. Human supervision first and foremost requires people to be able to understand how the AI system arrived at its results and how to perhaps steer the outputs in other, more acceptable directions. The central question within the ATM community (and beyond) is therefore: How to best design and employ AI methods in ATM operations such that they provide optimal results in terms of operational safety and efficiency, while being consistent, predictable and understandable?
In this PhD research, you will answer the above-mentioned question by comparing heuristic/structured optimization methods with (Deep) Reinforcement Learning methods. Besides quantifying and comparing these approaches in terms of safety and efficiency, you will also specifically focus on their explainability and interpretability potential, as these play important roles in human understanding. The (Python-based) BlueSky open- source ATM simulator will play a central role in both implementing and assessing the considered AI methods, while assessing explainability and interpretability may require interface design and human evaluations using other software platforms.
Next to your thesis work you will also work in the AI4REAL-NET project, where you'll cooperate in an international (Horizon Europe, EU-funded) consortium of industrial and academic partners. This will give you the opportunity to already during your PhD build an extensive research and industry network.
You will be working in the Control and Simulation (C&S) section of the faculty of Aerospace Engineering. The C&S section of the faculty of Aerospace Engineering aims to advance the development of autonomous control systems and combined human-machine systems in aerospace, building on a solid theoretical basis and physical insights while exploiting theoretical progress in adjacent fields, and to validate these systems experimentally in world-class facilities, effectively closing the loop between theory and practice.
C&S aims to be a leading research group in the integration, development and testing of new theories on control, autonomous and cognitive systems (with and without human elements).
RequirementsThe PhD position is funded by the Horizon-Europe AI4REAL-NET project. You will be working in an international consortium, which means that good proficiency in the English language (spoken and written) is required. Furthermore, the position requires:
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.
Conditions of employmentDoctoral 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 € 2770 per month in the first year to € 3539 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.
TU Delft (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 as one of our core values and we actively engage to be a university where you feel at home and can flourish. We value different perspectives and qualities. We believe this makes our work more innovative, the TU Delft community more vibrant and the world more just. Together, we imagine, invent and create solutions using technology to have a positive impact on a global scale. That is why we invite you to apply. Your application will receive fair consideration.
Challenge. Change. Impact!
Faculty Aerospace EngineeringThe Faculty of Aerospace Engineering at Delft University of Technology is one of the world's most highly ranked (and most comprehensive) research, education and innovation communities devoted entirely to aerospace engineering. More than 200 science staff, around 270 PhD candidates and close to 3000 BSc and MSc students apply aerospace engineering disciplines to address the global societal challenges that threaten us today, climate change without doubt being the most important. Our focal subjects: sustainable aerospace, big data and artificial intelligence, bio-inspired engineering and smart instruments and systems. Working at the faculty means working together. With partners in other faculties, knowledge institutes, governments and industry, both aerospace and non-aerospace. Working in field labs and innovation hubs on our university campus and beyond.
Click here to go to the website of the Faculty of Aerospace Engineering.
Additional informationFor more information about this vacancy, please contact Joost Ellerbroek, Assistant Professor, email: [email protected].
Application procedureAre you interested in this vacancy? Please apply before 1 October 2023 via the application button and upload your motivation and CV.
Faculty/Department
Faculty of Aerospace EngineeringJob Type
PhDScientific field
EngineeringHours per week
38Salary
€ 2.770,00 - € 3.539,00Desired level of education
University graduateVacancy number
TUD04270Method of applying
Via systemChallenge:Improve flight efficiency and safety.
Change:Utilize explainable AI (XAI) techniques.
Impact:Contribute to sustainable aviation.
Job descriptionPressing economic, capacity, and environmental concerns are forcing a fundamental redesign of the Air Traffic Management (ATM) system that currently relies heavily on an expert and skilled human workforce. Given that Artificial Intelligence (AI) is expected to transform every aspect of modern society, the ATM community is also considering the introduction of AI-based systems to cope with more stringent safety, environmental and economic constraints. Here, AI is expected to have most impact on long-term, strategic flight planning by providing solutions to both existing (e.g., using historical data) and new (e.g., using reinforcement learning) problems. However, given that AI also needs to satisfy requirements related to reliability, output predictability and ethics, human involvement and supervision remain of paramount important for decades to come. Human supervision first and foremost requires people to be able to understand how the AI system arrived at its results and how to perhaps steer the outputs in other, more acceptable directions. The central question within the ATM community (and beyond) is therefore: How to best design and employ AI methods in ATM operations such that they provide optimal results in terms of operational safety and efficiency, while being consistent, predictable and understandable?
In this PhD research, you will answer the above-mentioned question by comparing heuristic/structured optimization methods with (Deep) Reinforcement Learning methods. Besides quantifying and comparing these approaches in terms of safety and efficiency, you will also specifically focus on their explainability and interpretability potential, as these play important roles in human understanding. The (Python-based) BlueSky open- source ATM simulator will play a central role in both implementing and assessing the considered AI methods, while assessing explainability and interpretability may require interface design and human evaluations using other software platforms.
Next to your thesis work you will also work in the AI4REAL-NET project, where you'll cooperate in an international (Horizon Europe, EU-funded) consortium of industrial and academic partners. This will give you the opportunity to already during your PhD build an extensive research and industry network.
You will be working in the Control and Simulation (C&S) section of the faculty of Aerospace Engineering. The C&S section of the faculty of Aerospace Engineering aims to advance the development of autonomous control systems and combined human-machine systems in aerospace, building on a solid theoretical basis and physical insights while exploiting theoretical progress in adjacent fields, and to validate these systems experimentally in world-class facilities, effectively closing the loop between theory and practice.
C&S aims to be a leading research group in the integration, development and testing of new theories on control, autonomous and cognitive systems (with and without human elements).
RequirementsThe PhD position is funded by the Horizon-Europe AI4REAL-NET project. You will be working in an international consortium, which means that good proficiency in the English language (spoken and written) is required. Furthermore, the position requires:
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.
Conditions of employmentDoctoral 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 € 2770 per month in the first year to € 3539 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.
TU Delft (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 as one of our core values and we actively engage to be a university where you feel at home and can flourish. We value different perspectives and qualities. We believe this makes our work more innovative, the TU Delft community more vibrant and the world more just. Together, we imagine, invent and create solutions using technology to have a positive impact on a global scale. That is why we invite you to apply. Your application will receive fair consideration.
Challenge. Change. Impact!
Faculty Aerospace EngineeringThe Faculty of Aerospace Engineering at Delft University of Technology is one of the world's most highly ranked (and most comprehensive) research, education and innovation communities devoted entirely to aerospace engineering. More than 200 science staff, around 270 PhD candidates and close to 3000 BSc and MSc students apply aerospace engineering disciplines to address the global societal challenges that threaten us today, climate change without doubt being the most important. Our focal subjects: sustainable aerospace, big data and artificial intelligence, bio-inspired engineering and smart instruments and systems. Working at the faculty means working together. With partners in other faculties, knowledge institutes, governments and industry, both aerospace and non-aerospace. Working in field labs and innovation hubs on our university campus and beyond.
Click here to go to the website of the Faculty of Aerospace Engineering.
Additional informationFor more information about this vacancy, please contact Joost Ellerbroek, Assistant Professor, email: [email protected].
Application procedureAre you interested in this vacancy? Please apply before 1 October 2023 via the application button and upload your motivation and CV.