Assistant Professor for Digital Assessment and Learning Analytics (Tenure Track)

TU Delft

Challenge: Supporting educators in assessment

Change: Human-machine cooperation on hybrid performance assessment

Impact: Accurate assessment, classification and diagnosis of human behaviour


Job description

Assessment is one of the most important and rapidly changing fields in digital education. Research into data driven user modelling, adaptive systems and personalized assessment build on recent developments in AI technologies. This enables future scenarios for human-machine cooperation on hybrid performance assessment and also supports educators in assessment. Applications are currently developed in fields from mathematics education, programming education, writing assessment as multi-modal behavior analysis.

Innovations in assessment driven by tracking and sensor data are becoming more and more important in the diagnosis and assessment of human behaviour and performance. From analysing learning tracking data in online systems and social media to inferring human characteristics and behaviour online, this has also extended to human interaction with sensor systems and IoT networks. This has recently been addressed in multi-modal learning analytics and performance support systems.

We want to strengthen the diversity of our team with an ambitious, enthusiastic assistant professor which will be making a significant contribution to research in digital education.

This role is affiliated and connected to the Leiden-Delft-Erasmus Centre for Education and Learning (LDE-CEL) and the 4TU.Centre for Engineering Education.These Centres are bundling efforts and partners of the TU Delft for Research, Development and Innovation in Digital Education. They bring together an interdisciplinary team of Computer Science, Learning Science, Psychology and Learning Engineering experts to conceptualize, develop, evaluate and pilot educational innovation projects in cooperation with all partners.

As assistant professor you will work with an enthusiastic team and the networks of the Dutch 4TU federation as also the Leiden-Delft-Erasmus partnership. You will come into a highly innovative interdisciplinary environment expecting high quality research and education in digital education and data science. You will work in national and international highly visible research groups and networks and enthusiastic teams in different faculties working on research for strengthening and applying latest innovation in teaching and learning for students and educators.

In this position you will research methods for using interaction and tracking data from diverse online and IoT sources for assessment, classification and diagnosis of human behaviour.

This includes:

  • using social media and online user traces for inference and modelling of human traits;
  • using sensor data and interaction with embedded devices for skills and competence assessment;
  • using statistical and machine learning methods for data integration and classification;
  • using simulation and computational models for data generation;
  • designing real-time feedback and interaction loops as also interactive machine learning approaches.



  • A solid background in AI, machine learning, software engineering and data science, interdisciplinary project experience
  • Research expertise in the topics of machine learning, sensor-based interaction and assessment in educational technologies
  • Experience and publications in relevant fields of data science and learning science, learning analytics, computer-based assessment
  • Education experience in data science, machine learning, computer-based assessment or comparable
  • An interest to develop and teach modules in learning analytics and assessment and an interest in working with BSc and MSc level student of different disciplines on research and software development projects
  • Strong social skills including listening, conflict resolution, coaching, inclusivity, support and experience in coaching student groups as also MSc thesis
  • An enthusiastic team player, curious about new forms of education and assessment
  • Postdoc experience and PhD co-supervision is a plus.


Conditions of employment

A tenure-track position is offered for six years. In the fifth year we’ll decide if you will be offered a permanent faculty position, based on performance indicators agreed upon at the start of the appointment. We expect that you have the potential to grow towards an Associate Professor and/or Full Professor role in the future.

Inspiring, excellent education is our central aim. We expect you to obtain a University Teaching Qualification (UTQ) within three years if you have less than five years of teaching experience. This is provided by the TU Delft UTQ programme.
TU Delft sets high standards for the English competency of the teaching staff. The TU Delft offers training to improve English competency. If you do not speak Dutch, we offer courses to learn the Dutch language within three years.

Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities. The TU Delft offers a customisable compensation package, a discount 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. An International Children’s Centre offers childcare and there is an international primary school.


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 and aim to be as inclusive as possible (see our Code of Conduct). Together, we imagine, invent and create solutions using technology to have a positive impact on a global scale.

Challenge. Change. Impact!


Additional information

For more information about this vacancy, please contact Professor Marcus Specht at


Application procedure

Are you interested in this vacancy? Please apply before September 30, 2021 via the application button and upload the following:

  • An application letter
  • Your CV
  • A research statement
  • A teaching statement
  • A diversity statement

Please list at least two references that we may approach as part of your application procedure.

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

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