PhD Candidate for Hybrid Human-AI Regulation

Website Adaptive Learning Lab, Radboud University

PhD Candidate for Hybrid Human-AI Regulation: supporting young learners’ self-regulated learning skills

  • Employment: 1.0 FTE
  • Maximum gross monthly salary: € 3,061
  • Faculty of Social Sciences
  • Required background: Research University Degree
  • Duration of the contract: 4 years
  • Application deadline: 22 March 2021

We are looking for

We are looking for a PhD candidate to work on the ERC-funded HHAIR project for 4 years.  HHAIR stands for Hybrid Human-AI Regulation and is directed at developing a new tool to support young learners’ self-regulated learning skills.

Hybrid systems that combine artificial and human intelligence hold great promise for training human skills. In this project we will develop a Hybrid Human-AI Regulation (HHAIR) to support young learners’ Self-Regulated Learning (SRL) skills within Adaptive Learning Technologies (ALTs). HHAIR targets young learners (10-14 years) for whom SRL skills are critical in today’s society. Many of these learners use ALTs, such as Gynzy, to learn mathematics and languages every day in school. ALTs optimise learning based on learners’ performance data but even the most sophisticated ALTs fail to support SRL. In fact, most ALTs take over (offload) control and monitoring from learners. HHAIR on the other hand aims to gradually transfer regulation of learning from AI-regulation to self-regulation. Learners will increasingly regulate their own learning progressing through different degrees of hybrid regulation. In this way, HHAIR supports optimised learning and transfer and development of SRL skills for lifelong learning. This project is groundbreaking in developing the first hybrid systems to train human SRL skills with AI.

The design of HHAIR starts with investigating ALTs’ trace data in exploratory studies (WP1), applying these insights to develop HHAIR in design studies (WP2), investigating immediate effects on deep learning in short-term field studies (WP3) and effects on SRL skills for future learning in long-term field studies (WP4). The AI@EDU infrastructure will connect HHAIR to ALTs used daily in schools across Europe. As a PhD candidate you will develop advanced measurement of SRL and an algorithm to drive hybrid regulation for developing SRL skills in young learners.

The HHAIR team consists of Dr Inge Molenaar (Educational Science), Dr Max Hinne (Artificial Intelligence) and Prof. Eliane Segers (Educational Science), a postdoctoral researcher, and two PhD candidates. The full project description is available upon request.

We ask

We are looking for a recent Master’s graduate in a relevant field, for instance, educational science, educational psychology, behavioural science, artificial intelligence, or any other relevant discipline. You should have:

  • Profound knowledge of self-regulated learning in the context of technology-enhanced learning.
  • The ability to set up and execute field studies in schools with students.
  • Outstanding methodological and analytical qualities, and experience with collecting and analysing data.
  • Ideally have experience with writing academic publications.
  • Experience with designing educational interventions which is needed for the design of personalised dashboards.
  • A basic understanding of artificial intelligence and machine learning would be an advantage for the collaboration with the PhD candidate in AI and postdoctoral researcher.
  • Good collaboration skills and an excellent command of the English language, both spoken and written, are needed to work on this interdisciplinary project.
  • Basic Dutch language proficiency is needed for working with young learners at the schools involved.

We are

The Faculty of Social Sciences is one of the largest faculties at Radboud University (Nijmegen, Netherlands). The faculty currently employs about 650 employees. The faculty’s ambition is to become one of the top social science institutes in Europe, providing high-quality research programmes and study programmes that rank among the best in the Netherlands.

The Behavioural Science Institute (BSI) is part of the Faculty of Social Sciences. BSI is a multidisciplinary behavioural research institute where researchers collaborate across the boundaries of psychology, educational science and communication science. It has seven research programmes covering three main research themes: (1) development and learning, (2) psychopathology, health and well-being, and 3) social processes and communication. BSI conducts applied/translational research as well as fundamental research. The BSI Graduate School (recognised by the Netherlands Organisation for Scientific Research) is responsible for the training of PhD candidates. BSI has state-of-the-art research facilities for observational studies, experiments, eye-tracking studies, EEG measurements and GSR recording, psychobiological research, and behavioural measurements in both real and 3D virtual environments.

You will work within BSI’s Learning and Plasticity group. This programme deals with the micro-analysis of learning processes. The project is situated in the Adaptive Learning Lab (ALL) which is a technologically intensive research lab that is recognised as a pioneer in developing innovative learning technologies applying Learning Analytics and Artificial Intelligence techniques. ALL currently consists of 1 postdoctoral researcher, 2 junior researchers and 6 PhD candidates, and is led by Associate Professor Inge Molenaar. ALL conducts research in different educational contexts, with projects in primary education, secondary education and higher education. Moreover, ALL collaborates with a number of international partners in the EARLI Centre of Innovative Research (E-CIR). We offer a highly innovative context at an advanced research university with ample opportunities to travel, publish and develop yourself over the course of this project.

Radboud University

We want to get the best out of science, others and ourselves. Why? Because this is what the world around us desperately needs. Leading research and education make an indispensable contribution to a healthy, free world with equal opportunities for all. This is what unites the more than 22,000 students and 5,000 employees at Radboud University. And this requires even more talent, collaboration and lifelong learning. You have a part to play!

We offer

  • Employment: 1.0 FTE.
  • The gross starting salary amounts to €2,395 per month based on a 38-hour working week, and will increase to €3,061 in the fourth year (salary scale P).
  • In addition to the salary: an 8% holiday allowance and an 8.3% end-of-year bonus.
  • Duration of the contract: you will be appointed for an initial period of 18 months, after which your performance will be evaluated. If the evaluation is positive, the contract will be extended by 2.5 years (4 year contract).
  • Your teaching duties may be up to 10% of your employment.
  • The intended start date is 1 May 2021.
  • You will be able to use our Dual Career and Family Care Services. Our Dual Career and Family Care Officer can assist you with family-related support, help your partner or spouse prepare for the local labour market, provide customized support in their search for employment  and help your family settle in Nijmegen.
  • Have a look at our excellent employment conditions. They include a good work-life balance (among other things because of the excellent leave arrangements), opportunities for development and a great pension scheme.

Would you like more information?

For more information about this vacancy, please contact:
Inge Molenaar, Associate Professor
Tel.: (+31) 6 208 866 16

Apply directly

Please address your application to Inge Molenaar and submit it, using the application button, no later than 22 March 2021, 23:59 Amsterdam Time Zone.

Your application should include the following attachments:

  • Letter of motivation.
  • CV.

The first round of interviews will take place on Thursday 1 April. The second round of interviews will take place on Thursday 22 April.


We drafted this vacancy to find and hire our new colleague ourselves. Recruitment agencies are kindly requested to refrain from responding.

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