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Université du Luxembourg
Doctoral Researcher in Machine Learning Security & TestingUniversité du Luxembourg • Kirchberg Campus, Kirchberg Campus, LU
Doctoral Researcher in Machine Learning Security & Testing

Doctoral Researcher in Machine Learning Security & Testing

Université du Luxembourg • Kirchberg Campus, Kirchberg Campus, LU
Il y a plus de 30 jours
Description de poste

Your role

The position holder will be required to perform the following tasks/will do research on the following topics:

  • Software engineering practices for machine learning
  • Define quality and security principles for machine learning systems
  • Design and implement technical testing algorithms to assess these systems in real-world conditions

The candidate will contribute to both fundamental research and the development of practical software platforms and demonstrators in collaboration with industrial and public-sector partners. More generally, the PhD thesis is part of a large initiative at Serval and SnT, which aims to support the reliable deployment of AI systems by providing industry actors with practical evaluation tools, such as technical testing platforms for AI.

The successful candidate will join the SERVAL research group and contribute to research and development activities at the intersection of Agentic AI, AI Security, Trustworthy AI, Software Engineering, and Cybersecurity. The group is developing novel methods, tools, and platforms to support the safe deployment of AI systems in real-world environments. Current research activities focus on topics such as:

  • AI agents and computer-use agents
  • Security, robustness, and trustworthiness of AI systems
  • Evaluation, benchmarking, and testing of AI systems
  • Runtime monitoring and governance of AI agents
  • Formal specification and verification techniques for AI-enabled systems
  • AI systems for enterprise and cybersecurity applications
  • AI compliance, risk assessment, and trustworthy AI engineering

Your profile

  • Master in Computer Science. Major in machine learning, software engineering or software security
  • Strong programming skills
  • Strong analytical skills
  • Industry experience in information and communication technology will be considered as an advantage
  • Commitment, team working, a critical mind, and motivation are skills that are more than welcome
  • Knowledge of both the basics and the latest developments of machine learning, in particular large language models and agentic framewoks will be considered a strong asset
  • Operational Language Requirements: Fluent written and verbal communication skills in English are required

Academic Eligibility (Thesis):

Applicants must demonstrate at least B2-level proficiency in the language of their thesis. For details and accepted certificates, please visit the Application for admission – Doctoral Candidates.

Important Note: Due to the specific requirements for this position and due to the constraints of the project, please note that we are only able to consider applicants from EU EEA/EFTA countries, or NATO nations, or NATO Indo-Pacific Partners (Australia, Japan, Rep South Korea, New Zealand), and Ukraine.

We offer

  • A modern, dynamic university with a personal and inclusive atmosphere. Multilingual and international character. Staff coming from more than 90 countries. Member of The Guild of European Research Intensive Universities
  • An exceptional research environment, supported by skilled staff and high-quality equipment. Strong links to professional sectors and the Luxembourg labour market. A unique urban campus with excellent infrastructure
  • A partner for society and industry. Cooperation with European institutions, innovative companies, the Financial Centre and a wide range of non-academic partners including ministries, local governments, associations, and NGOs

How to apply

Applications should include:

  • Curriculum Vitae
  • Cover letter presenting your motivation for this doctoral thesis topic, and explaining how your qualifications and aspirations align with its academic focus
  • Transcript of all modules and results from university-level courses taken
  • Research statement and topics of particular interest to the candidate (300 words)

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.

All qualified individuals are encouraged to apply. In line with our values, the University of Luxembourg promotes an inclusive culture. We encourage applications from individuals of all backgrounds and are dedicated to upholding equality and respect for our employees and students.

Gender equality:In line with our values, the University of Luxembourg encourages an inclusive culture. We promote equality of opportunity, diversity and a working and learning environment in which the rights and dignity of everybody is respected. The University is committed to achieving gender parity among its academic staff. Should candidates present equivalent CVs, preference will be given to female candidates in all departments where gender parity is not yet achieved.

General information:

  • Contract Type: Fixed Term Contract 36 Month
  • Work Hours: Full Time 40.0 Hours per Week
  • Location: Kirchberg Campus
  • Internal Title: Doctoral Researcher
  • Job Reference: UOL08325

The yearly gross salary for every Doctoral researcher at the UL is EUR 44531 (full time).

About us

The University of Luxembourg is an international research university with a distinctly multilingual and interdisciplinary character.

The Interdisciplinary Centre for Security, Reliability and Trust (SnT) at the University of Luxembourg is a leading international research and innovation centre in secure, reliable and trustworthy ICT systems and services.We play an instrumental role in Europe by fueling innovation through research partnerships with industry, boosting R&D investments leading to economic growth, and attracting highly qualified talent. We look for researchers from diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular Networks, and ICT Services & Applications.

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Doctoral Researcher in Machine Learning Security & Testing • Kirchberg Campus, Kirchberg Campus, LU

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