Join our research effort with a four-year PhD position on AI in Education in the context of the Dutch National Lab on AI in Education (NOLAI). In this PhD you will aim to develop a framework for learner modelling services. For this, you will develop methods to determine and compare the quality of various services for different learner modelling approaches and use these methods to help researchers and teachers decide which learner modelling approach and services to use in which situations. In this position you will be part of the Software Technology for Learning and Teaching research group of the department of Information and Computing Sciences of Utrecht University.

The bigger picture focusses on a simple question: what do students need to learn more efficiently? The educational sciences have studied this extensively, and we know a lot about student learning. Some of the most important aspects of learning are intrinsic and extrinsic motivation, self-regulated and peer-assisted learning, and elaborated feedback. For almost all these learning aspects, teachers or software applications need to diagnose the students’ learning paths and provide feedback. Not only the students’ progress and approach to learning, but also which steps to take next, taking the learning goals into account. However, the plethora of platforms and tools used in blended learning environments threatens the quality of personalised feedback. Amongst others, teachers find it difficult to monitor student progress and to determine what students need in online environments.

The needs of a student learning depend on their current knowledge and skills. There are many approaches to model the learner in this sense (e.g., based on ELO ratings or Bayesian models), but their granularity and services provided to model the learner can differ significantly, affecting, amongst others, when and how they are best employed.

This research project will take place within the Dutch National Lab on AI in Education in which schools, companies, and (applied) universities collaborate to take the next steps in supporting learning in primary and secondary education. 

Excited to join our efforts? Bring multiple of the following and join our team:

• a master’s degree in Artificial Intelligence, Computer Science, Data Science, Information Science or related fields (or graduation from one within the next months);
• a strong interest in conducting research in the area of AI in education;
• experience with state of the art technologies for AI and ML;
• experience in interacting with stakeholders and end-users to understand their requirements;
• an interest in performing experiments with various approaches to using AI in education;
• good communicative skills in English, both in writing and speech;
• good critical thinking and collaboration skills.

You will be offered:

• A position for 4 years;
• A full-time gross salary ranging from € 2541,- to € 3247,- in scale P;
• Benefits including 8% holiday bonus and 8.3% end-of-year bonus;
• A pension scheme, partially paid parental leave, and flexible employment conditions based on the Collective Labour Agreement Dutch Universities.

In addition to the employment conditions laid down in the CAO for Dutch Universities, Utrecht University has a number of its own arrangements. For example, there are agreements on professional development, leave arrangements and sports. We also give you the opportunity to expand your terms of employment yourself via the Employment Conditions Selection Model. This is how we like to encourage you to continue to grow.

More information about working at the Faculty of Science can be found here.

Sharing science, shaping tomorrow. A better future for everyone. This ambition motivates our scientists in executing their leading research and inspiring teaching. At Utrecht University, the various disciplines collaborate intensively towards major strategic themes. Our focus is on Dynamics of Youth, Institutions for Open Societies, Life Sciences and Sustainability.

At the Faculty of Science, there are 6 departments to make a fundamental connection with: Biology, Chemistry, Information and Computing Sciences, Mathematics, Pharmaceutical Sciences and Physics. Each of these is made up of distinct institutes that work together to focus on answering some of humanity’s most pressing challenges. More fundamental still are the individual research groups – the building blocks of our ambitious scientific projects. For more information, please visit working at the Faculty of Science. 

The position is within the Software Technology for Learning and Teaching research group of the department of Information and Computing Sciences of Utrecht University. The position is funded by the NOLAI growth fund project, which is hosted by the Radboud University Nijmegen. We expect the PhD candidate to divide their time over the two locations. The main supervisor of the PhD candidate will be dr. Johan Jeuring from Utrecht University, but the PhD candidate will also be supervised by dr. Serge Thill and dr. Inge Molenaar from Radboud University, and collaborate with other PhD candidates and Postdocs working in NOLAI.

The Dutch Education Lab for Artificial Intelligence (NOLAI) is a consortium including schools, (applied) universities and companies, that aims to develop innovative intelligent technologies that help improve the quality of primary and secondary education over the next ten years. With these innovations, the increasing demand for responsible innovation with intelligent technologies in the public sector education are met. NOLAI is organisationally embedded in the Faculty of Social Sciences of Radboud University and consists on the one hand of a scientific programme (where researchers and data-scientists work) and on the other hand of a co-creation programme (in which education, science and business work collaboratively on projects). In total about thirty to forty people will be working at NOLAI and many more people will be involved in carrying out the co-creation projects.