Are you eager to improve the reliability of complex, safety-critical systems through formal methods? This PhD position offers the opportunity to develop new analysis techniques for reliability models and algorithms for probabilistic model checking, implement them in tools and apply them in industrial settings.

We offer a 5-year long PhD-TA (PhD-Teaching Assistant) position to work on probabilistic model checking techniques for safety-critical systems.

Our research goal is to improve the safety and reliability of complex, safety-critical systems using formal methods. Certifying that systems, such as autonomous vehicles, storm surge barriers, trains, and robotic systems, operate safely and reliably is a major challenge today. In our research, we develop rigorous, automated techniques for modelling and analysing safety-critical systems. We implement our solutions in tools such as the model checkers Storm and mCRL2, and apply our techniques in industrial settings.

We are looking for a highly motivated candidate to develop new analysis techniques to ensure safe and reliable operation of complex systems. Within the PhD position, you will develop new analysis techniques for reliability models and create and improve algorithms for probabilistic model checking. You will implement these techniques in tools such as the Storm model checker, and apply and evaluate them in industrial context. The specific research topic can be influenced by your personal interests. Possible research directions include:

• Variant management in reliability models: developing techniques to efficiently find optimal system designs.
• Data-driven reliability models: automated creation and adaptation of reliability models (such as fault trees and Markov chains) from data.
• Extensions of continuous-time Markov chains: developing more realistic models by extending Markov chains with, for example, fixed time delays, uncertainty, or varying failure rates.

You will contribute to the research of the Formal System Analysis group. We offer an exciting research environment in our group with national and international collaborators and industrial contacts. Our research combines theoretical contributions with tool implementations and industrial applications.

This is a Teaching PhD position with a 25% teaching load. Throughout your PhD, you will spend some time helping with the teaching of relevant courses, for example running instruction sessions and correcting student homework. You will also have the opportunity to obtain teaching qualifications.

• A master's degree (or an equivalent university degree) in Computer Science, Mathematics, or a related field.
• Strong interest in formal methods.
• Experience in software development (C++, Python) is preferred.
• A research-oriented attitude.
• Ability to work in an interdisciplinary team and interested in collaborating with industrial partners.
• Initiative and motivation to work independently. 
• Motivated to develop your teaching skills and coach students.
• Fluent in spoken and written English (C1 level).

A meaningful job in a dynamic and ambitious university, in an interdisciplinary setting and within an international network. You will work on a beautiful, green campus within walking distance of the central train station. In addition, we offer you:

• Full-time employment for five years, with an intermediate evaluation (go/no-go) after nine months. You will spend 25% of your employment on teaching tasks.
• Salary and benefits (such as a pension scheme, paid pregnancy and maternity leave, partially paid parental leave) in accordance with the Collective Labour Agreement for Dutch Universities, scale P (min. €2,872 max. €3,670).
• A year-end bonus of 8.3% and annual vacation pay of 8%.
• High-quality training programs and other support to grow into a self-aware, autonomous scientific researcher. At TU/e we challenge you to take charge of your own learning process.
• An excellent technical infrastructure, on-campus children's day care and sports facilities.
• An allowance for commuting, working from home and internet costs.
• A Staff Immigration Team and a tax compensation scheme (the 30% facility) for international candidates.