PhD Position in Data Systems Education

Job description

Do you have passion for students and education, and a drive to explore the Data Systems Education landscape? Do you enjoy solving both technical and educational challenges? The Intelligent Data Engineering lab (INDElab) is looking for a PhD candidate.
Join Us!
We are looking for a highly motivated candidate to continue our exploration of the Data Systems Education (DSE) landscape. We approach Data Systems broadly, from query languages to modelling and dependencies, and from Big Data to individual spreadsheets. The education side is also broadly construed and can focus from K-12 all the way through to life-long learning. Our aim is to build theory on the principles behind DSE, and discover in what ways it is similar to, or different from, other disciplines within Computing Education. At this moment, we are less interested in applications such as learning analytics and LLM-supported education.
As this is an open-ended vacancy, please share which aspect of DSE research you are most passionate about in your application materials, and how it connects to our current work in this space.
This is what you will do
Here are some of your responsibilities:
conducting independent research resulting in academic publications in peer-reviewed international conferences or journals;
designing and performing qualitative studies to understand the principles behind Data Systems Education;
develop models or tools that support Data Systems Education;
assist in teaching of at least one course;
supervising Bachelor and Master thesis projects;
complete your PhD thesis in four years.
What we ask of you
We are looking for someone who is passionate about both technology and education. You should also have:
a MSc in Computer Science or Engineering, Information Studies, Human-Technology Interaction, Educational Science, or similar;
strong analytical thinking skills;
basic programming skills;
the ability to work well individually, as well as collaboratively;
good communication skills in oral and written English;
broad experience with qualitative research methods is a plus;
Dutch language is a plus.
This is what we offer you
A temporary contract for 38 hours per week for the duration of 4 years (the initial contract will be for a period of 18 months and after satisfactory evaluation it will be extended for a total duration of 4 years). The preferred starting date is as soon as possible. This should lead to a dissertation (PhD thesis). We will draft an educational plan that includes attendance of courses and (international) meetings. We also expect you to assist in teaching undergraduates and master students.
The gross monthly salary, based on 38 hours per week and dependent on relevant experience, ranges between € 3,204 to € 4,051 (scale P). On top of this, you receive 8% holiday allowance and 8,3% year-end allowance. The UFO profile PhD Candidate is applicable. A favourable tax agreement, the ‘30% ruling’, may apply to non-Dutch applicants. The
Collective Labour Agreement of Universities of the Netherlands is applicable.
Read more about our extensive secondary benefits package.
You will work in this team
The
Faculty of Science has a student body of around 8,000, as well as 1,800 members of staff working in education, research or support services. Researchers and students at the Faculty of Science are fascinated by every aspect of how the world works, be it elementary particles, the birth of the universe or the functioning of the brain.
The mission of the
Informatics Institute
(IvI) is to perform curiosity-driven and use-inspired fundamental research in Computer Science. The main research themes are Artificial Intelligence, Computational Science and Systems and Network Engineering. Our research involves complex information systems at large, with a focus on collaborative, data driven, computational and intelligent systems, all with a strong interactive component.
You will work in the
Intelligent Data Engineering lab
(INDElab) where we investigate intelligent systems that support people in their work with data and information from diverse sources. This includes addressing problems related to the preparation, management, integration and reuse of data. We perform both applied and fundamental research, informed by empirical insights into data science practice. You will work closely together with dr. Daphne Miedema.
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