The Formal Methods and Tools group at the University of Twente is looking for a highly motivated and talented PhD candidate to join the team working on software modelling, model-driven system engineering and model transformations. The successful candidate will work on a cutting-edge research project on intelligent diagnostics. In particular, the work will be about finding ways to specify diagnosable monitoring systems, to identify models with the best diagnostic potential, to describe available knowledge to facilitate diagnostics, to define diagnostic algorithms, and to combine domain knowledge and system knowledge to provide diagnosability guarantees.

You will be working on the ZORRO project: Engineering for Zero Downtime in Cyber-Physical Systems via Intelligent Diagnostics, led by Prof. Dr. Mariëlle Stoelinga. The project is a collaboration between the University of Twente, VU Amsterdam, Saxion University of Applied Sciences, TNO-ESI and five industrial partners. Two of the PhD positions in this project will be working at the Formal Methods & Tools group, the other one on the topic of knowledge engineering. This PhD position will be supervised by Dr. Vadim Zaytsev and Dr. Marcus Gerhold.

Responsibilities:

• Conduct independent research in the area of software modelling, model-driven system engineering, and model transformations.
• Collaborate with a team of researchers and experts in the field to contribute to the development of new techniques and approaches.
• Publish research results in leading academic journals and present findings at international conferences.
• Engage in critical analysis and evaluation of existing theories and methods in the field.
• Supervise and mentor involved BSc and MSc students as needed.

• You have, or will shortly acquire, a MSc degree in computer science, software engineering, or a related field.
• You have a creative mindset and excellent analytical and communication skills.
• You have some background in software modelling, model-driven system engineering, or model transformations, and are willing to delve deeper into these topics.
• You have excellent programming skills and experience with relevant tools and technologies.
• You are fluent in English and have strong problem-solving and analytical skills.
• You have good team spirit and like to work in an interdisciplinary and internationally oriented environment, collaborating within the industry and academia alike.

• As a PhD student at the University of Twente, you will be appointed to a full-time position for four years, with a qualifier in the first year, within a very stimulating and exciting scientific environment;
• The University offers a dynamic ecosystem with enthusiastic colleagues;
• Your salary and associated conditions are in accordance with the collective labour agreement for Dutch universities (CAO-NU);
• You will receive a gross monthly salary ranging from € 2.541,- (first year) to € 3.247,- (fourth year);
• There are excellent benefits including a holiday allowance of 8% of the gross annual salary, an end-of-year bonus of 8.3%, and a solid pension scheme;
• The flexibility to work (partially) from home;
• A minimum of 232 leave hours in case of full-time employment based on a formal workweek of 38 hours. A full-time employment in practice means 40 hours a week, therefore resulting in 96 extra leave hours on an annual basis.
• Free access to sports facilities on campus;
• A family-friendly institution that offers parental leave (both paid and unpaid);
• You will have a training programme as part of the Twente Graduate School where you and your supervisors will determine a plan for a suitable education and supervision;
• We encourage a high degree of responsibility and independence, while collaborating with close colleagues, researchers and other staff.
• Starting date of the position: 1 September 2023.

The FMT group is part of the Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) at the University of Twente. Our central goal is to develop formal techniques and tools to support the development of complex systems, and increase the reliability of the high-tech systems that we all rely on, both as individuals and as society.