PhD Position Multimodal modeling of Trust Development for Trust Calibration in AI

Study how to enable AI systems to understand human trust development during human-AI collaboration through multi-modal modeling, allowing for improved trust calibration. 

 

Job description

Hybrid Intelligence (HI) is the combination of human and artificial intelligence (AI), augmenting human intellect instead of replacing it, and developing AI which works with and for humans.

 

Hybrid Intelligent AI systems should actively calibrate the trust they elicit from humans they interact with by actively identifying cases of over/under-trust, and then acting to address these. To do this, they require an understanding of their human partners’ trust perceptions and how these dynamically evolve. Currently, trust perceptions are typically measured using explicit assessments, such as questionnaires at static moment in time. However, such measures lack efficiency in providing feedback for trust calibration in human-AI interactions, and effectiveness because they struggle to capture fine-grained information about how human trust perceptions dynamically evolve. 

 

In this project, you will be working to address this issue by developing approaches using multimodal sensor data for the implicit assessment of human trust perceptions.  In particular, you will work on answering the following research question: How can we enable artificial intelligence systems to efficiently and effectively assess the dynamic development of humans’ trust evaluations during collaboration for improved calibration behavior? 

 

Given the recent advances in multimodal language modeling (e.g., MLLMs), this project will explore approaches that leverage unstructured language data describing elements of human trust perceptions and associated reasoning processes during interactions captured with a “Think Aloud” (TA) protocol. The project will involve collecting multimodal data about trust behavior; identifying data collection approaches for effective and efficient modeling of trust perceptions and calibration; and addressing a cycle of trust behavior, from understanding human trust, to adjusting agent behavior, which in turn influences human trust.

 

This project will be supervised by dr. Bernd Dudzik and dr. Myrthe Tielman. That means the candidate will be a part of both the research group of Pattern Recognition and Interactive Intelligence, both within the Intelligent Systems section of Computer Science, EEMCS. Additional co-supervisors will be Prof. Dr. Mark Neerincx (II, TU Delft & TNO) and Prof. Dr. Dan Balliet (VU Amsterdam).

 

This project is part of a larger research effort within the Hybrid Intelligence Center, where you will have the opportunity to collaborate with researchers across multiple universities and disciplines. 

 

Job requirements

We are looking for a candidate who meets the following essential criteria:

  • A Master’s degree or equivalent (or about to graduate with one) in a relevant field (Artificial Intelligence, Computer Science, Data Science, Cognitive Science, etc.)
  • A good command of spoken & written English 
  • A curiosity-driven mindset and a willingness to learn
  • Some experience with ML or NLP 
  • Some experience in collecting multimodal datasets or running experiments with human subjects

We encourage you to apply even if you do not meet all the criteria above as long as you are willing to acquire the relevant skills.

 

Additionally, the following criteria are appreciated:

  • Experience with interdisciplinary research projects.
  • Strong analytical and conceptual modelling competencies  
  • Good programming skills (preferably Python), including ML methods and libraries.  

 

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 Electrical Engineering, Mathematics and Computer Science 

The Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) brings together three scientific disciplines. Combined, they reinforce each other and are the driving force behind the technology we all use in our daily lives. Technology such as the electricity grid, which our faculty is helping to make completely sustainable and future-proof. At the same time, we are developing the chips and sensors of the future, whilst also setting the foundations for the software technologies to run on this new generation of equipment – which of course includes AI. Meanwhile we are pushing the limits of applied mathematics, for example mapping out disease processes using single cell data, and using mathematics to simulate gigantic ash plumes after a volcanic eruption. In other words: there is plenty of room at the faculty for ground-breaking research. We educate innovative engineers and have excellent labs and facilities that underline our strong international position. In total, more than 1000 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.

 

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 € 2901 per month in the first year to € 3707 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 a monthly work costs contribution. Flexible work schedules can be arranged.  

 

Will you need to relocate to the Netherlands for this job? TU Delft is committed to make your move as smooth as possible! The HR unit, Coming to Delft Service, offers information on their website to help you prepare your relocation. In addition, Coming to Delft Service organises events to help you settle in the Netherlands, and expand your (social) network in Delft. A Dual Career Programme is available, to support your accompanying partner with their job search in the Netherlands.  

 

Additional information
If you would like more information about this vacancy or the selection procedure, please contact dr. Myrthe Tielman and dr. Bernd Dudzik, via m.l.tielman@tudelft.nl or b.j.w.dudzik@tudelft.nl.

 

Application procedure

Apply via the application button and upload: 

  1. your CV, 
  2. a motivation letter describing both your personal motivation for applying for this particular PhD position, and why you believe you will be a good candidate, 
  3. degree transcripts including information about courses you've followed if relevant to the project, 
  4. the names and contact information (email & phone nr) of two referees.  If completed and relevant, please also include
  5. your Msc. Thesis.

 

The screening of candidates will occur as applications arrive. If shortlisted, you will be contacted before the closing date of the vacancy. Interested candidates are encouraged to apply as soon as possible and before June 30 2025.
 

Note that this job opening is one of several job openings on the [HI page with job openings](https://www.hybrid-intelligence-centre.nl/recruitment/). You can apply to more than just this one. If you do so, please inform the Hybrid Intelligence Centre’s [Project Manager via email](sendto:projectmanager.at.HI@gmail.com) of the projects you are applying to.

 

We aim to create hybrid intelligence for everyone, see also our Diversity Statement. To do this, we need an inclusive and diverse team of researchers. We especially encourage people from underrepresented groups to apply for this job.

 

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

 

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.
  • For the final candidates, a knowledge security check will be part of the application procedure. For more information on this check, please consult Chapter 8 of the National Knowledge Security Guidelines. We carry out this check on the basis of legitimate interest.
  • Please do not contact us for unsolicited services
Faculty/Department:  Faculty of Electrical Engineering, Mathematics & Computer Science
Salary range:  €2901 - €3707
Hours per week:  36-40
FTE:  1.0
Submission is possible until:  30 Jun 2025
ID job:  2312