PhD in Machine Learning Official Statistics

PhD Candidate in Machine Learning for Official Statistics Contract Type:

Fixed Term Contract

36 Month

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. Welook 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.

As the successful candidate, you will primarily contribute to a partnership project with STATEC, the National Statistics Institute in Luxembourg. The successful candidate will join the Security, Reasoning and Validation (Serval) research group and work on a research project related to the application of machine learning for official statistics. The subject of the thesis will be “Exploring Large Language Models for Data-to-Text Problems” and involves the study of technical methods and approaches for adapting large language models to tasks mixing text and structured data, such as statistical report generation and semantic search across historical statistics publications.

Successful PhD candidates will extensively explore and analyse the suitability and potential benefits of LLMs (and other machine learning models) in these tasks. These investigations include the feasibility, practicality and success evaluation of prototype implementations. More generally, the PhD thesis is part of a large initiative at Serval and SnT, which aims to support the reliable deployment of machine learning systems by providing industry actors with practical tools.

The team you will be working with:

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

• Software engineering practices for machine learning
• Tabular machine learning
• Large language models on structured data

PhD Student Role:
Under the direction of their supervisor, the candidate will carry out research activities and write a thesis with the main goal of obtain a PhD in the area of machine learning. This includes conducting literature surveys and establishing state-of-the-art; developing necessary experimental and simulation facilities where required; planning, executing, and analyzing experiments and simulations; conducting joint and independent research activities;

contributing to project deliverables, milestones, demonstrations, and meetings; disseminating results at international scientific conferences/workshops and peer reviewed scientific publications.

• Master in Computer Science. Major in machine learning or software engineering is an asset
• 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 other generative AI models

Language

Skills:

Fluent written and verbal communication skills in English are required. French is a plus

• 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 …

Applicati…