The TU Delft Software Engineering Research Group has the following vacancies:
Assistant or associate professor in Software Engineering
The group’s research aims at obtaining a deep understanding of how people develop software and use the tools of the trade. Based on which we create methods, techniques, theories and software tools advancing and accelerating software development. In your role as assistant/associate professor you will develop and realise your vision on software engineering. You may focus on any research domain in software engineering. Our existing domains, which you may join, range from empirical software engineering, software architecture, evolution, testing and deployment, to the application of AI and social software engineering. Alternatively, you may propose a complementary domain based on your expertise, or take on a wider research scope, integrating multiple domains.
We stimulate you to build your team of PhD students, whom you’ll supervise and coach to completion. You will also teach our top-level international Bachelor and Master students, and supervise their graduation projects. Playing an active role in our committees and the scientific community, you will transfer knowledge and help strengthen our Faculty, Department and Research Group. At SERG, you’ll join an internationally diverse, thirty-strong team of highly motivated women and men: PhD students, post-docs and Assistant, Associate and Full Professors. We’ll give you all the support, training and coaching you need to evolve and grow your career in our open and friendly environment.
Deadline November 26th, 2022
I want to know more or apply immediately…
Contact: Andy Zaidman (firstname.lastname@example.org)
PhD student in Software Testing and Validation for AI-intense Systems
The Ph.D. position will focus on the research and development of solutions to test and validate AI-intensive systems. AI-intensive systems involve multiple internal stages, pipelines, models, as well as interaction with other non-AI-based components. Often, they also process multimodal data requiring human interpretation. The question of quality assurance for AI thus is more refined than a single evaluation or testing approach, which often is seen today. In this Ph.D. project, we therefore will focus on bridging evaluation and testing methodologies from the software engineering and applied machine learning domains.
This project is a collaboration between the Multimedia Computing (MMC) Group at the Intelligent Systems (INSY) Department, and the Software Engineering Research Group (SERG) at the Software Technology (ST) Department. The INSY and ST departments closely work together in the faculty’s Computer Science research and education.
Contact: Annibale Panichella (email@example.com)
PhD student in Software Testing
The Software Engineering Research Group (SERG) has recently acquired a NWO Vici grant called TestShift. The Vici grant is the most prestigious personal research grant from the Dutch Science Foundation NWO and will reinforce the software testing research line at Delft University of Technology.
For this project we are seeking enthusiastic Master students interested in obtaining a PhD degree in the cross-section of software testing, human computer interaction, and socio-technical factors in software engineering. The prospective PhD student is expected to do high-quality research: coming up with creative solutions, working diligently to iron out all details and getting a deeper understanding, interacting with peers around the world, but also interacting with practitioners from both the open source and industrial domain to evaluate your research.
TestShift is rooted in empirical software engineering and will make use of research methods such as ethnography, longitudinal field studies and case studies.
Contact: Andy Zaidman (firstname.lastname@example.org)
PhD student in Testing Distributed Systems
Modern computation increasingly depends on large-scale distributed systems and blockchains. However, these systems are difficult to design and implement correctly. They may fail to ensure correctness in subtle executions with unexpected orderings of exchanged messages, network partitions, and process failures.
The PhD project aims to develop program analysis and testing techniques for improving reliability of distributed systems and blockchains.
The project lies in the intersection of software testing, program analysis, and distributed systems. The prospective PhD student is expected to do high-quality research involving both theory and implementation: getting a deep understanding of theoretical abstractions of fault-tolerant systems and developing novel software analysis and testing techniques.
Contact: Burcu Kulahcioglu Ozkan (email@example.com)