Research Scientist in Machine Learning and Big Data

About the FDEF

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

The Faculty of Law, Economics and Finance (FDEF) at the University of Luxembourg offers a unique academic and research environment.

Rooted in Luxembourg but with a European and international outlook, teaching and research benefit from the proximity of the European institutions, Luxembourg's leading international financial centre and its vibrant business community. Institutional and private sector partnerships, sponsored Chairs and a growing network of international partner universities make the FDEF a dynamic academic hub at the heart of Europe.

Your role

The candidate is expected to develop and pursue an independent research agenda in the field of economics, with a particular focus on the application of machine learning and big data methods. The position involves producing high-quality, peer-reviewed research suitable for publication in leading international journals, as well as seeking external research funding and contributing to interdisciplinary collaborative projects within and beyond the department. The successful candidate will actively contribute to teaching at undergraduate and / or master's levels. This may include, for example, core contributions to courses in applied econometrics, machine learning, computational economics, and big data analytics. In line with the department's strategic focus on digital transformation and data-driven policy, the candidate is expected to engage with academic, institutional, and external stakeholders in Luxembourg and internationally, including policymakers, regulators, and research organizations.

Your profile

The ideal candidate applies machine learning and big data techniques to important questions in economics, combining advanced computational methods with sound economic theory to uncover insights that traditional methods cannot. Candidates should demonstrate a clear, coherent, and forward-looking research agenda with strong potential for publication in leading international journals.

Applicants should have a robust background in quantitative methods, including causal inference and econometric modeling, as well as familiarity with modern computational tools such as machine learning, text analysis, and large-scale data infrastructures. An interest in applying these techniques to a wide range of economic domains - such as macroeconomic forecasting, labor markets, financial stability, development, health, environmental and energy economics, or public policy - is particularly relevant.

Experience in teaching at undergraduate and graduate levels is appreciated, ideally including courses on applied econometrics, computational economics, or data-driven decision-making. The candidate should also be able to supervise master's theses and research projects and foster students' ability to critically apply advanced quantitative and computational methods to real-world economic and policy challenges.

In particular, the following requirements apply :

• PhD in Economics with a demonstrated specialization in Machine Learning and Big Data applications
• Willingness to work in an inter-cultural and international environment and collaborate across disciplines
• Have the linguistic skills to evolve in a multilingual environment : fluency in either English or French, good understanding of the second language and possibly a third language, German in particular, will be considered an advantage

We offer

How to apply

Applications should include :

Early application is highly encouraged, as the applications will be processed upon reception. To ensure full consideration, please ONLINE formally through the HR system by January 31, 2026. 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 :