An academic in Quantitative Finance

An academic in Quantitative Finance : Innovation and Transition

Reference: 38704 / LSM 011 / 2027

UCLouvain seeks to recruit

A full-time academic position in Quantitative Finance : Innovation and Transition

Main campus:

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.

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:

You will teach mainly in the AFIN field (accounting and finance) within the Louvain School of Management (LSM). You will teach in the various study cycles managed by the faculty. You will also supervise master's theses. You may be required to teach courses outside your direct area of expertise (e.g. general management courses, or courses of a quantitative nature) and, to a lesser extent, on campuses other than that linked to your main assignment, and on a staggered timetable. The teaching load is delivered in English and French at the bachelor's and master's levels, across the two campuses of the faculty, 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.

You will develop your research activities, including leading research programs, in the field of finance, studied using data-driven and quantitative approaches. With this in mind, you will explore the concepts of innovation and transition in a very broad sense: technological innovations, including AI, and other innovations in the field of financial engineering on the one hand; and transition in the environmental, social and governance sense on the other. You will play an active role within the Louvain Institute for Data Analysis and Modeling (LIDAM) and the Louvain Finance (LFIN Pole) by participating in various events (seminars, workshops, etc.). You will also supervise Ph.D. theses.

Once tenured, you 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.

You 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

You have a PhD in Management, Economics or Finance or in another field (engineering, statistics, actuarial science, etc.) but have worked on financial applications. As part of your research, you have worked with modern quantitative analysis tools. Fields of application of particular relevance to us include – but are not limited to: AI and machine learning, data science, fintech, energy, climate and environment.

You have experience of teaching at university level, preferably supported by formal assessment. If not, you have teaching skills (presentations to audiences of various sizes). Your research experience is evidenced by international publications. You have a good ne