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 

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.

Research

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.

In addition …

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

Education

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. 

Experience

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 network of scientific collaborators in different countries, as evidenced by publications or research partnerships (academic and/or with the associative or private sector). Ideally, you have completed a significant stay or experience abroad, outside the institution where you obtained your PhD.

Skills

You are comfortable working as part of a team of academics and integrate research results into your teaching. You are capable of conducting high-level scientific research, from obtaining funding to team management. You are creative, open to pedagogical innovation and multidisciplinary. You are familiar with modern tools in the field of statistics, econometrics and data analysis in general.

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)

Important note regarding applications

When sharing these job opportunities through your channels, please make it clear that applications must be submitted exclusively via the official website.
To apply, candidates should click on the job title in the link below and then select “Apply”.
Applications submitted through any other channel cannot be considered.

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> We study homogeneous diffusion martingales evolving in a bounded state space D = [a,b], where aand bare zeros of the diffusion coefficient. We call a process of the form Zt = E[B | Ft], with B a Bernoulli random variable, a Bernoulli-Doob martingale. Our main results establish a complete equivalence: every such diffusion martingale is a Bernoulli-Doob martingale (Theorem 2) and, conversely, every continuous time-homogeneous Markov Bernoulli-Doob martingale on a Brownian filtration arises from such a diffusion (Theorem 3). The intuitive reason is that a bounded martingale has constant expectation while accumulating variance, so it converges to the maximum-variance distribution with given mean and range, namely the Bernoulli. We further show that this Bernoulli limit is truly asymptotic: for any fixed finite horizon T, the probability of not yet having reached the boundary is strictly positive (Theorem 4), even when the individual boundaries are accessible. We clarify the relationship between Feller’s boundary classification, the pathwise SDE framework, and the martingale constraint, showing that the martingale property forces absorption at any attainable boundary. The theory is illustrated with the Φ-martingale, the Jacobi martingale, and applications to credit-risk modelling.

Arnaud Germain (LFIN)

At the intersection of finance and machine learning, PhD researcher Arnaud Germain is developing new ways to identify early warning signs of corporate default.

As part of his PhD at UCLouvain and the Louvain Finance Center, under the supervision of Professor Frédéric Vrins, his research focuses on credit risk: predicting which firms are more likely to experience financial trouble.

Instead of relying on one single global model, he groups similar firms together and builds more targeted prediction models, while also accounting for changing macroeconomic conditions.

In today’s uncertain economic environment, earlier detection of financial distress can make a real difference for financial institutions.

After completing his PhD, Arnaud will join NEOMA Business School as Assistant Professor, continuing research that combines methodological innovation with real-world impact.

L'UCLouvain recrute un·e assistant·e (F/H/X) en "Accounting & Finance"

Entrée en fonction : 15 septembre 2026

Qualifications requises :

- Diplôme de master en sciences économiques, en sciences de gestion, en ingénieur de gestion, ou diplôme équivalent obtenu avec mention au minimum équivalente à la distinction.
- Capacité et motivation à s’intégrer dans une équipe d’enseignement ainsi que dans une équipe de recherche.
- Capacité et motivation à développer des aptitudes pédagogiques dans le cadre de l’enseignement universitaire.
- Bonne maîtrise de la langue française et/ou de l’anglais (niveau B2).
- Aptitude de communication.
- Sens de l’initiative et des responsabilités.
- Être capable d’enseigner en langue française. A défaut, cette condition apparaîtra clairement lors du premier renouvellement du mandat de deux ans.

Les candidatures sont à soumettre en ligne jusqu’au 22 mai 2026 incl.

   MORE INFO