Doctoral Researcher in Machine Learning for Official Statistics
Explore large language models for data-to-text tasks in official statistics with a 36-month PhD position at the University of Luxembourg.
Best for:Best for recent computer science graduates with a strong background in machine learning, software engineering, and a passion for applying AI to structured data challenges in official statistics.
Overview
This PhD position at the University of Luxembourg focuses on applying machine learning and large language models to transform structured statistical data into textual outputs, such as reports and semantic search. The successful candidate will join the Security, Reasoning and Validation (Serval) research group within the Interdisciplinary Centre for Security, Reliability and Trust (SnT), collaborating with STATEC, the National Statistics Institute of Luxembourg. The project aims to develop practical tools for reliable machine learning deployment in official statistics, addressing challenges like statistical report generation and semantic search across historical publications. The role involves cutting-edge research, prototype development, and contributions to broader initiatives in trustworthy AI systems.
What you'll do
- Develop and evaluate technical methods for adapting large language models to tasks combining text and structured data, such as statistical report generation and semantic search.
- Conduct feasibility studies and prototype implementations to assess the practicality and success of ML/LLM applications in official statistics.
- Collaborate with STATEC, the National Statistics Institute of Luxembourg, to integrate research findings into real-world statistical workflows.
- Contribute to broader initiatives at SnT aimed at supporting the reliable deployment of machine learning systems in industry.
- Present research findings at academic conferences and workshops, and publish results in peer-reviewed journals.
- Work in a multidisciplinary team to explore the suitability and benefits of LLMs for data-intensive tasks in official statistics.
Requirements
Degree required: Master's degree in Computer Science or a related field; a major in machine learning or software engineering is highly advantageous
Degree offered: PhD
Language: Fluent written and verbal communication skills in English; at least B2-level proficiency in the language of the thesis (French is a plus)
Instruction: English
- Strong programming skills (e.g., Python, Java, or similar)
- Proven expertise in machine learning, particularly large language models and generative AI
- Familiarity with software engineering practices for machine learning systems
- Experience with tabular data processing and machine learning applications
- Strong analytical and problem-solving skills
- Applicants must meet the academic eligibility criteria for doctoral candidates at the University of Luxembourg, including language proficiency requirements
- No specific nationality or residency restrictions mentioned, but adherence to university admission policies applies
Funding & terms
How to apply
Applicants must submit their application online through the University of Luxembourg’s HR system. The application should include a CV, a cover letter explaining motivation and alignment with the thesis focus, transcripts of university-level courses, and a research statement (300 words). Early applications are highly encouraged as they will be processed upon reception. Email applications will not be considered.
- Curriculum Vitae (CV)
- Cover letter presenting motivation and alignment with the thesis topic
- Transcript of all university-level courses taken
- Research statement (300 words) outlining topics of interest
Contact
Maxime Cordy· Research Supervisor
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