PhD Candidate in Automata Learning

1.0 FTE
Gross monthly salary
€ 2,770 - € 3,539
Required background
Research University Degree
Organizational unit
Faculty of Science
Application deadline
Are you an aspiring researcher, fascinated by theoretical computer science? And would you like to conduct research at the intersection of automata learning, testing, and category theory? As a PhD candidate, you will help boost the scalability of automata learning through the development of approximation and abstraction methods in learning algorithms and the underlying theory.

You will contribute to model learning, which is a family of techniques for automatically constructing automata models of black-box systems, by systematically running tests and making observations. These techniques have been applied to analyse network protocols, legacy software, smart card readers and embedded control software. As a PhD candidate on this project, you will help to boost the scalability of automata learning through the development of approximation and abstraction methods in learning algorithms and the underlying theory. Your research will have a strong focus on developing the foundations of automata learning, using category theory and coalgebra as a formalism of choice, enabling a broad application of the results. As such, you will conduct research at the intersection of automata learning, testing and category theory.

This PhD position is part of an NWO VIDI project called Approximation, Abstraction and Apartness in Automata Learning (APPLE). For details, see here and feel free to contact us with any questions about the project and position. You will be supervised by Jurriaan Rot.

The start of the project is flexible (sometime between November and the summer of 2024). If you have not yet fully completed your Master's degree but are excited about this position, please do not hesitate to apply or contact us.
Your teaching load may be up to 10% of your working time.


  • You should hold an MSc or equivalent degree in Computer Science, Mathematics or a closely related field, or expect to obtain such a degree in this academic year.
  • You are able to work both independently and as part of a team.
  • You are proficient in English. (Dutch is not required.)
  • Prior knowledge of either category theory or automata learning is appreciated but not required.

We are

The position is available in the Software Science group of the Institute for Computing and Information Sciences (iCIS) at Radboud University. Our mission is to conduct top research on the use of models for design and analysis of software, bridging the gap between theory and applications. The Software Science group has extensive expertise in model learning and testing and theoretical computer science in general.

The Faculty of Science is a complete science faculty where research and education are closely related. The faculty aims to be an academic community with an international character, where staff members from different backgrounds combine their talents with the common goal of being a leading faculty of science in Europe.

Radboud University

We are keen to meet critical thinkers who want to look closer at what really matters. People who, from their expertise, wish to contribute to a healthy, free world with equal opportunities for all. This ambition unites more than 24,000 students and 5,600 employees at Radboud University and requires even more talent, collaboration and lifelong learning. You have a part to play!

We offer

  • It concerns an employment for 1.0 FTE.
  • The gross starting salary amounts to €2,770 per month based on a 38-hour working week, and will increase to €3,539 in the fourth year (salary scale P).
  • You will receive 8% holiday allowance and 8.3% end-of-year bonus.
  • You will be employed 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).
  • 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.
  • Working for us means getting extra days off. In case of full-time employment, you can choose between 30 or 41 days of annual leave instead of the legally allotted 20.

Additional employment conditions

Work and science require good employment practices. This is reflected in Radboud University's primary and secondary employment conditions. You can make arrangements for the best possible work-life balance with flexible working hours, various leave arrangements and working from home. You are also able to compose part of your employment conditions yourself, for example, exchange income for extra leave days and receive a reimbursement for your sports subscription. And of course, we offer a good pension plan. You are given plenty of room and responsibility to develop your talents and realise your ambitions. Therefore, we provide various training and development schemes.

Would you like more information?

For questions about the position, please contact Jurriaan Rot, Associate Professor at +31 24 365 21 23 or jrot [at] (jrot[at]cs[dot]ru[dot]nl).

Practical information and applying

You can apply until 24 September 2023, exclusively using the button below. Kindly address your application to Jurriaan Rot. Please fill in the application form and attach the following documents:
  • A letter of motivation.
  • Your CV, including the contact details of two scientific staff members. 
  • Transcript of grades.
The first round of online interviews will take place on Friday 6 October. You would preferably begin employment as soon as possible.

We can imagine you're curious about our application procedure. It offers a rough outline of what you can expect during the application process, how we handle your personal data and how we deal with internal and external candidates.
Apply now Application deadline

We would like to recruit our new colleague ourselves. Acquisition in response to this vacancy will not be appreciated.

Contact information

Associate Professor
+31 24 365 21 23

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