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"Postdoc in Automated Software Testing with Generative AI"

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Postdoc in Automated Software Testing with Generative AI

Postdoc in Automated Software Testing with Generative AI

The successful candidate will join the SVV research group headed by Prof. Domenico Bianculli. The team focuses on the development and design of reliable, safe, and secure software systems, carrying out both upstream activities such as requirements quality assurance and architecture analysis, as well as downstream verification & validation activities, such as software testing and runtime verification. For further information, you may refer to https://www.uni.lu/snt-en/research-groups/svv

The successful candidate will work with Prof. Fabrizio Pastore on several activities concerning the application of generative AI to automate the testing of software systems.

The position holder will be required to perform the following tasks:

  • Carrying out research in the predefined areas
  • Managing and contributing to national and international research projects
  • Preparing project deliverables
  • Disseminating results through scientific publications
  • Presenting results in well-known international conferences and workshops
  • Implementing proof-of-concept solutions
  • Providing guidance to PhD, MSc, and BSc students
  • Organizing relevant workshops and demonstrations
  • Contributing to the acquisition of research funding

Your profile...

The candidate should possess a PhD degree in Computer Science, Software Engineering or a related field. The ideal candidate should have some knowledge and experience in the following topics:

  • Large Language Models and Multimodal Language Models
  • Generative Networks and Diffusion Models
  • Program Analysis
  • Software Testing Automation

The candidate should have critical thinking and team working skills. Fluent written and verbal communication skills in English are required. The candidate should demonstrate interest in publishing in high-ranked software engineering conferences and journals.

In return you will get…

Multilingual and international character. Modern institution with a personal atmosphere. Staff coming from 90 countries. Member of the "University of the Greater Region" (UniGR). A modern and dynamic university. High-quality equipment. Close ties to the business world and to the Luxembourg labour market. A unique urban site with excellent infrastructure. A partner for society and industry. Cooperation with European institutions, innovative companies, the Financial Centre and with numerous non-academic partners such as ministries, local governments, associations, NGOs …

How to apply...

Applications should include: Curriculum Vitae (including work experience, list of publications), Cover letter indicating the research area of interest and your motivation, Research statement. Early application is highly encouraged, as the applications will be processed upon reception. Please apply ONLINE formally through the HR system. Applications by Email will not be considered. The University of Luxembourg is committed to achieving gender parity among its staff. Should candidates present equivalent profiles, preference will be given to female candidates in all departments where gender parity is not yet achieved. The University of Luxembourg embraces inclusion and diversity as key values. We are fully committed to removing any discriminatory barrier related to gender, and not only, in recruitment and career progression of our staff.

General Information: Contract Type: Fixed Term Contract 12 Months, Work Hours: Full Time 40.0 Hours per Week, Location: Kirchberg Campus, Internal Title: Postdoctoral Researcher, Job Reference: UOL07621. The yearly gross salary for every Postdoctoral Researcher at the UL is EUR 85176 (full time).

Job details: Title: Postdoc in Automated Software Testing with Generative AI, Employer: University of Luxembourg, Location: Luxembourg, Luxembourg, Published: 2025-07-25, Application deadline: Unspecified, Job type: Postdoc, Field: Computational Engineering, Artificial Intelligence, Programming Languages, Software Engineering, Machine Learning.

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