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Université Catholique de Louvain

An academic in Optimization and Learning for Data-Driven Decision systems

등록일 : 2026-09-08
마감일
2026.11.05(목) 20:00D-21
기관유형
대학
학력
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직군
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통계/수학,일반/산업공학,컴퓨터/통신,정치/국제관계/행정
근무지
Wallonia
근무유형
풀타임
근무형태
Full-time academic position; tenure after positive assessment of the probationary period – typically four years.
근무시간
Teaching load capped at 90 hours for a full-time tenure-track position, and 150 hours once tenured.
급여액
An attractive and progressive salary according to seniority and the promotion process.
Organization Logo
기관명Université Catholique de Louvain
홈페이지http://www.uclouvain.be
유형대학

Reference: 38690 / LSM 067 / 2027

UCLouvain seeks to recruit

A full-time academic position in Optimization and Learning for Data-Driven Decision systems

Main campus: Louvain-la-Neuve

About us

UCLouvain is the leading French-speaking university in Belgium and is also widely recognised internationally. Founded in the heart of Europe in 1425, the university brings together 40,000 students and 6,000 staff members on nine campuses in Brussels and Wallonia. Research and education activities are organised in 20 faculties, 23 research institutes, 5 learning centres and 18 libraries. UCLouvain also has two university hospitals.

UCLouvain is a major player in the transition to a sustainable society. The challenges of the ecological crisis are integrated into courses and the university develops numerous local projects (such as a university farm and sustainable campuses). As a digital university, UCLouvain is involved in open science and education, and trains academics in innovative teaching practices through its Louvain Learning Lab. Thanks to two science parks, the university’s research benefits from interaction with 250 companies and 3 incubators, which is fuelled further by being at the centre of a region driven by technological innovation.

UCLouvain has a strong tradition of international collaboration in both teaching and research. These partnerships take shape through numerous exchange agreements, its firm commitment to the European alliance Circle U. and the network The Guild, as well as the welcoming of a large community of international researchers, supported by the Louvain Welcome Desk.

The University's staff policy is based on five pairs of values which are fundamental pillars of the way the University operates, works and lives together: https://uclouvain.be/fr/emploi/politique-personnel.html

Post description

Within the Louvain School of Management (LSM) and the Louvain Institute of Data Analysis and Modeling in economics and statistics (LIDAM), Social Sciences and Humanities Sector, this position will include the following teaching, research and community service duties:

  • Teaching


    To develop, in future managers, high-levels skills in coding, optimization, and learning-based decision methodologie, the current course portfolio includes programming, operations research, artificial intelligence, and quantitative decision making. The teaching load is delivered in English and French at the bachelor's and master's levels, across the two campuses of the Louvain School of Management (LSM), located in Louvain-la-Neuve and Mons. Overall, your presence will help to expand the capacity for supervising dissertations and diversify teaching approaches, whilst ensuring a stronger interdisciplinary presence.

  • Research


    To develop a strong and internationally visible research agenda centered on mathematical optimization and its integration with data science and machine learning for decision systems, research areas of interest include advanced optimization methods (linear, integer, stochastic, robust, distributionally robust, and chance-constrained); predictive and prescriptive analytics bridging forecasting and decision-making; learning-integrated decision frameworks (predict-then-optimize, decision-focused learning, reinforcement learning); and algorithmic decision models combining mathematical programming with AI techniques.


    The successful candidate is expected to play an active role within the Louvain Institute for Data Analysis and Modeling (LIDAM), and more specifically in the Center for Operations Research and Econometrics (CORE), by participating in academic events, publishing in leading journals in operations research, mathematical programming and machine learning, supervising doctoral students, and actively collaborating with researchers from the Center for Operations Research and Econometrics (CORE), and more generally from the Louvain Institute for Data Analysis and Modeling (LIDAM), as well as those from the Institute of Information and Communication Technologies, Electronics, and Applied Mathematics (ICTEAM).

  • In addition …


    Once tenured, the successful candidate will carry out various service activities and responsibilities within the institution, such as being a member of a programme committee or examination committee or having management responsibilities within the faculty or research institute.


    The successful candidate will also contribute to serving society, particularly in the economic, social, cultural or development cooperation fields. Finally, you will ensure, through research and teaching activities, the university’s international visibility.

Who we’re looking for

  • Education


    You have a PhD in Operations Research, Applied Mathematics, Systems Engineering, Computer Science, Management Engineering, or a closely related quantitative field.

  • Experience


    You have a proven track record in university teaching, with evidence where possible by formal evaluations. You can demonstrate a strong and independent research track record, with publications in leading international journals, or clear potential to publish, in operations research, mathematical programming, learning-based optimization, or machine learning. You have a strong core identity rooted in mathematical programming and operations research. Experience in securing competitive research funding and supervising doctoral students will be considered a strong asset.

  • Skills


    You will bring expertise in the theory, algorithms, and modeling frameworks of mathematical optimization, with a research identity centered on advancing the methodological foundations of decision systems. You are able to make original contributions to optimization methods, whether in integer and stochastic programming, robust and distributionally robust optimization, or the principled integration of learning and optimization through frameworks such as predict-then-optimize, decision-focused learning, or reinforcement learning for sequential decision-making, and you are motivated by the challenge of building a unified methodological bridge between mathematical programming and modern data science. Specific experience in data-driven and learning-driven approaches to modeling and optimization will be considered as a strong asset.


    You will be expected to become an active and contributing member of the research community of CORE and, more broadly, of LIDAM, enriching its methodological culture through contributions that advance the algorithmic and theoretical foundations of optimization and its integration with machine learning and AI.


    You can communicate in French and English. If this is not the case, you undertake to acquire a command of these two languages within two years of taking up your position. Knowledge of other languages is an asset.

What we offer

  • Tenure after positive assessment of the probationary period – typically four years. This type of career entitles you to a public sector pension.
  • Appointment as lecturer or professor according to your previous academic experience, as determined by the Rectoral Council.
  • Teaching load capped at 90 hours for a full-time tenure-track position, and 150 hours once tenured.
  • An attractive and progressive salary according to seniority and the promotion process.
  • A start date of 1 September 2027 at the earliest.
  • An integrated leadership and management training programme, including a range of pedagogical, linguistic and other training courses.
  • Benefits including transport, family, culture, commercial, etc.
  • Official policy that supports equal opportunities and promotes diversity within academic and all other categories of staff.
  • Specific emphasis on a work-life balance.

Practical Information

Application deadline: 5 November 2026 at noon (UTC+1 Time Zone)
Starting date: September 1st 2027

Location:

Social Sciences and Humanities Sector
(LSM) (https://uclouvain.be/en/faculties/LSM)
(IDAM) (https://uclouvain.be/en/research-institutes/IDAM)

Need more information?

Questions about this position:

Prof. Matthieu de Nanteuil, Dean LSM – doyen-lsm@uclouvain.be
Prof. Catherine Legrand, President IDAM – presidence-idam@uclouvain.be

Questions about the procedure:
Madam Céline Brauns, Rector’s Office, celine.brauns@uclouvain.be

Questions about online application:
Madam Andreea Chiriac, Rector’s Office, secretariat-vrpp@uclouvain.be

Interested?

Applications must be submitted exclusively via UCLouvain’s online recruitment system; submissions through other channels will not be considered.

Full details regarding the application procedure are available at: https://www.uclouvain.be/en/careers/submit-your-application

Applications must include one single PDF file containing the following documents:

  • a cover letter (to be included in the single PDF as well as in your candidate profile);
  • a detailed and up‑to‑date curriculum vitae (to be included in the single PDF as well as in your candidate profile);
  • a copy of the official doctoral degree certificate;
  • a complete publication list, including a summary of three recent and significant publications;
  • a teaching statement;
  • a research statement presenting the proposed research programme for the next five years.

Shortlisted candidates invited for an interview will subsequently be asked to provide:

  • a PhD project proposal, with a view to the possible recruitment of a doctoral candidate during the first year of appointment;
  • three to five letters of reference, submitted directly by referees according to the instructions provided by the University.

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