Doctoral Researcher in Human-Centred Governance of Learning AI Agents

Your role

The PhD student will contribute to a large industrial research collaboration with a major Luxembourgish energy utility, studying how organisations keep meaningful control over AI agents that learn from the people who use them. Once agents become ubiquitous across an organisation’s processes and continuously absorb feedback from everyday use, two questions become central: when should an agent take initiative rather than wait to be asked, and how does anyone know that its behaviour has not quietly shifted away from what was once validated.

The PhD addresses both. On the interaction side, it studies how an agent calibrates its own initiative so that it is helpful rather than intrusive, how it presents the choices it offers without overwhelming the person in front of it, and how it can act as a sparring partner that strengthens human judgment instead of quietly replacing it. On the control side, it develops methods for detecting behavioural drift in agents that keep learning, with quantitative measures of how far behaviour has moved from a validated baseline and mechanisms for returning to a trusted state without discarding genuine improvements. The topic examines how expertise, accountability and the shape of work itself change when an organisation delegates part of its regulated activity to agents at scale.

The work combines system building with empirical evaluation involving real users in operational settings. The student will collaborate closely with academic and industrial partners, and disseminate results through publications and project activities. The successful candidate will join the UBIX Research Group, led by Prof. Raphaël Frank.

You will be required to perform the following tasks:

• Carrying out research in the predefined areas
• Disseminating results through scientific publications
• Communicate and interact with the project team and industrial partners and report results
• Design and run empirical studies with real users in an industrial environment
• Implement and evaluate proof-of-concept software tools, and open-source them where possible

For further information about the role, please contact raphael.frank@uni.lu

Your profile

Qualification: The candidate should possess a MSc degree or equivalent in Computer Science or any related engineering discipline.

Experience: The ideal candidate should have some knowledge and/or experience in several of the following topics (ordered by importance):

• Large language models and LLM-based agents
• Human-AI interaction, human-computer interaction and human factors
• Reinforcement learning and learning from human feedback
• Behavioural and distribution drift detection, monitoring of deployed AI systems
• Evaluation and benchmarking of AI system behaviour
• Statistical anomaly detection
• Socio-technical or socio-economic study of technology adoption in organisations
• Trustworthy AI, AI governance and regulation

Information Technology Skills: Strong analytical and programming skills are required (Python and C/C++). Prior proven experience in data-driven innovation projects is an asset. Most importantly, you should be curiosity driven and willing to constantly learn new things!

Operational Language Requirements: Excellent command in English is required. Good working knowledge of either French, German or Luxembourgish (B1) is a plus

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.

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, including:
  • For each degree received or currently enrolled in, the degree, institution name, city, and country, and date (or expected date) of graduation
  • Title and short summary of final thesis
  • List of publications (if any)
  • If available, link to GitHub repository including completed open-source projects
• 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

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.

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: UOL08434

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.