Team Science and Innovation for Responsible Human-Centric AI


Job description

The most prominent challenges to AI are not only technical. Therefore, responsible Human-Centered Artificial Intelligence (HCAI), can only be the product of pluridisciplinary multi-stakeholder diverse collaborations. Collaborations within HCAI research, development, and production require new forms of teams and networks. Little attention has been given to the forms and dynamics of these new teams and the unprecedented challenges they face, as well as indicators of efficiency and success in these collaborations to reach responsible, sustainable, and trustworthy AI.

This PhD position focuses on the evolution of HCAI teams/networks from an anthropo-technical perspective. The candidate will be studying the forms and dynamics of collaborations between these teams/networks both in R&D and Production & Deployment of HCAI (AI components, AI systems, AI ecosystems). They will also investigate the influencing factors -internal and external– to achieve responsible AI as a culture and as a practice beyond ethical compliance. Internal factors may include team/network composition (e.g., diversity, size, structure) as well as the form of collaboration (e.g., type, timing, symmetry). External factors look at the environment where teams/networks form and collaborate, e.g., institutions, economic and political factors, etc.

The candidate will explore these questions at the intersection of AI, ethics, and team science, using different methodological approaches. These approaches may include (but at not restricted to):

  • Bibliometrics (scientific publications) and Altmetrics (citation, social networks, non-scientific publications) to investigate how researchers are influencing each other and how academic and research organizations are (Universities, Publishing companies, Tech companies R&D, funding national and international funding bodies) are influencing scientific (and R&D) teams;
  • Empirical investigation through interviews and surveys to understand existing forms of collaboration and the environment factors influencing these;
  • Agent-based modeling to investigate team dynamics and their influence on achieving responsible AI.

The expected outcomes of this research include (but are not limited to):

  • A taxonomy/forms of HCAI teams/networks collaborations: How did AI driven economy and academia reshape AI R&D and production and what are the requirements to produce responsible HCAI. How are these new models of collaborations different from the existing pluridisciplinary approaches (classified in the 90’s as cross-, multi, inter-, trance-disciplinary). The candidate will be re-thinking and extending this classification;
  • A taxonomy of HCAI teams/networks to bridge the knowledge gap in new teaming and collaboration forms and answer question such as “how are these new models of collaborations different from the existing pluridisciplinary approaches (classified in the 90s as cross-, multi, inter-, trance-disciplinary)”. The candidate will be re-thinking and extending this classification;
  • A conceptual framework (based on theoretical and empirical insights) that captures both the internal dynamics of these teams as well as the external factors fostering and shaping the collaborations. E.g., “how AI-driven economy and academia reshape AI R&D” and “how leadership styles influence the responsible HCAI as a culture”;
  • Policy/Guideline on teaming and collaboration best practices to build a responsible HCAI culture beyond ethical compliance.


For this position, we are looking for a candidate with excellent analytical skills. They/She/He must have a multidisciplinary background (e.g., computational social sciences, information system management). This project does not focus on building AI components; however, the candidate should be familiar with basic knowledge of the latest trends in AI techniques and willing to learn how these systems are developed, trained, and deployed. Experience with modeling techniques e.g., agent-based modeling or programming languages for data science and analytics (e.g., python, R, SQL, Julia) is preferred and knowledge of the fields of Healthcare-AI is a plus.

The candidate is expected to have good social skills, curiosity, and openness to collaborate with other researchers in the interdisciplinary environment of the faculty and to interact with stakeholders and policymakers along the PhD project.      

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 employment

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 we offer the Coming to Delft Service and Partner Career Advice to assist you with your relocation.

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 Technology, Policy and Management

With its excellent education and research at the intersection of technology, society and policy, the Faculty of TPM makes an important contribution to solving complex technical-social issues, such as energy transition, mobility, digitalisation, water management and (cyber) security. We combine insights from the engineering sciences, the social and the humanities. We develop robust models and designs, are internationally oriented and have an extensive network with knowledge institutions, companies, social organisations and governments.

Click here to go to the website of the Faculty of Technology, Policy and Management.

Additional information

For more information about this vacancy, please contact Nadia Metoui, e-mail: n.metoui@tudelft.nl (do not send your application to this email adress)

For information about the application procedure, please contact Olivie Beek, HR advisor, e-mail: recruitment-tbm@tudelft.nl

Application procedure

Please, submit your application online no later than 23 September 2022.

To apply, please submit the following:

  • Motivation letter (max 1 page), addressed to Nadia Metoui;
  • A short CV (max 2 pages);
  • An example of academic writing, paper, essay or part of your thesis.

Please note:

  • You can only apply online. We will not process applications sent by email and / or post;
  • Incomplete applications will not be processed;
  • A pre-Employment screening can be part of the selection procedure;
  • Acquisition in response to this vacancy is not appreciated.         


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截止日期 2022-09-23




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