Jobs – ULB – Postdoc in Data Science/Deep Learning/Big Data Mining for fraud detection

    Université Libre de Bruxelles (ULB)
    Computer science › Cybernetics
    Recognised Researcher (R2)
    01/06/2017 00:00 – Europe/Athens
    Belgium › Brussels

Position Description

Applications are invited for full-time post-doctoral (3 years) research position at the Machine Learning Group, Computer Science Department, Université Libre de Bruxelles, Belgium.

The vacancy is available to be filled in February (earliest) till April (at the latest). The researcher is expected to carry out fundamental research in Data Science/Machine Learning/Big Data Mining and to take an active role in an applied research project on deep learning for credit card fraud detection which is funding the position.

The Machine Learning Group, ULB is a research group that carries out theoretical research on statistical machine learning, predictive modeling and computational statistics, and takes part in several applied research projects in domains as diverse as big data mining, bioinformatics to biomedical engineering and fraud detection.

Located in heart of Brussels, the Université Libre de Bruxelles is renowned for quality research through its prestigious affiliate research centers and world renowned faculty. Brussels, the capital of Belgium and the European Union, is a cosmopolitan city renowned for its picturesque squares and buildings, serene parks and gardens and a very vibrant cultural life spiced up by many international languages.


Applicants are encouraged to apply as soon as possible as positions will remain open until filled by suitable candidates.


Candidates are invited to send their CV with the detailed list of publications, their PhD thesis and the name of at least 2 reference persons  in .pdf format by email to

The subject field of your email must include MLG-JOB: research position.

Equal Opportunity Employer

ULB is an equal opportunity employer and is committed to employing more handicapped individuals and especially encourages them to apply. ULB wishes to increase the proportion of women in areas in which they are underrepresented. Women are strongly encouraged to apply.

Web site for additional job details

Required Research Experiences

    Computer science › Cybernetics
    4 – 10

Offer Requirements

    Computer science: Master Degree or equivalent
    ENGLISH: Excellent


Applicants should have a recent PhD on a subject related to data mining, statistical machine learning or computational statistics. In particular, any research experience on data mining, machine learning, statistical analysis, or fraud detection will be an asset.

Applicants are expected to have strong programming skills, the ability to work independently, strong interpersonal skills, good writing and oral communication.

Upon offer of a position in MLG-ULB, the candidates who are non-EU citizens are required to obtain an appropriate long-term Schengen visa; further information is available from their nearest Belgian embassy.

Job – ULB – Postdoc in Machine Learning – 2 years


ULB MLG Brussels: Postdoc in machine learning, data science and big data for security (e.g. fraud detection)

2 year postdoc position


Research in big data and scalable machine learning with application to security problems (e.g. fraud detection) in the context of a project funded by Brussels Region.

Required skills:

  • you have a PhD in Machine Learning, Computational Science, (Bio)Engineering, Data Science, or equivalent.
  • Expertise in statistical machine learning, data mining, big data, map reduce, Spark, python, R programming.
  • Plus: expertise in application of big data mining to real problems, security applications, notably credit card fraud detection
  • You are fluent in English.
  • The successful applicant will be hosted by the Machine Learning Group, co-headed by Prof. Gianluca Bontempi.

    Starting date: asap
    For more information please contact Pr. Gianluca Bontempi, mail:
    Please send your CV, motivation letter and contact information for three references, publication list with indication of the citation number of each published paper.

Nr of positions available : 1

Research Fields

Computer science – Modelling tools

Career Stage

Experienced researcher or 4-10 yrs (Post-Doc)

Research Profiles

First Stage Researcher (R1)

Comment/web site for additional job details

Seminar- ULB – Context-sensitive Ordinal Regression Models for Human Facial Behaviour Analysis

    ULB  Machine Learning Group (MLG)
             S E M I N A R
       “Context-sensitive Ordinal Regression Models for Human Facial Behaviour Analysis”
       Wed 8 July 2015 from 11:30
       Université libre de Bruxelles,
       Campus de la Plaine (
       Département d’Informatique
       NO Building, Floor 8, local P.2NO8.08 (Rotule) (
       Boulevard du Triomphe – CP212
       1050 Bruxelles
Enabling computers to understand human facial behaviour has the potential to revolutionize many important areas such as clinical diagnosis, marketing, human computer interaction, and social robotics, to mention but a few. However, achieving this is challenging as human facial behaviour is a highly non-linear dynamic process driven by many internal and external factors, including ‘who’ the observed subject is, ‘what’ is his current task, and so on. All this makes the target problem highly context-sensitive, resulting in the changes of dynamics of human facial behaviour, which, in turn, is critical for interpretation and classification of target affective states (e.g., intensity levels of emotions or pain). In this talk, I will propose several extensions of the Conditional Ordinal Random Fields (CORF) model that are able to learn spatio-temporal and context-sensitive representations of human facial behaviour useful in various tasks of facial analysis. In particular, I will show how the proposed CORF models can be used for problems such as intensity estimation of facial expressions of emotion, intensity estimation of facial action units and facial expressions of pain. I will also demonstrate the performance of the models on the task of classification of facial expressions of persons with autism spectrum condition. Finally, I will discuss other potential applications of the models proposed and further challenges in modelling of human facial behaviour.
Ognjen Rudovic rreceived his PhD from Imperial College London, Computing Dept., UK, in 2014, a MSc degree in Computer Vision and Artificial Intelligence from Computer Vision Center (CVC), Barcelona, Spain, in 2008, and BSc in Automatic Control Theory from Electrical Engineering Dept., University Of Belgrade, Serbia, in 2006. He is currently working as a Research Fellow at the Computing Dept., Imperial College London, UK. His research interests include computer vision and machine learning, with a particular focus on face analysis, Bayesian learning and inference methods, and their application to human sensing. He is a member of Intelligent Behaviour Understanding Group (IBUG) at Imperial College London (
Pr. Gianluca Bontempi
co-Head of the Machine Learning Group
Département d’Informatique
Université Libre de Bruxelles
Boulevard du Triomphe – CP212
1050 Bruxelles, Belgium
Office Phone: +32-2-650 55 91
Fax: +32 2 650.56.09
Interuniversity Institute of Bioinformatics in Brussels (IB)²