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 email@example.com.
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.
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.
Faculty of Sciences, Department of Computer Science.
Required Qualifications :
PhD Degree (with doctoral thesis) in Computer Science, Bioinformatics, Computational Biology, Bioengineering, or equivalent qualifications.
Required Skills :
A minimum of 4-year scientific career at the time of hiring
Postdoctoral experience of minimum one year and an excellent scientific record
A stay abroad in an academic institution other that the one in which the doctoral studies were undertaken is mandatory. This can be during or after the doctoral studies. The academic stay abroad needs to have taken place either during a full academic year or maximum 4 academic stays adding up to a 12 month period
For non-French speaking natives, a learning period may be granted, but candidates must be capable of teaching in French (level C1 is required) at the end of the third year following their appointment.
The Faculty of Sciences of the Université Libre de Bruxelles (ULB) announces the opening of a full-time academic position in Data Science for Bioinformatics and Computational Biology starting October 1st, 2016. The position will be in affiliation with the Department of Computer Science of the ULB and the ULB/VUB Interuniversity Institute for Bioinformatics in Brussels (IB2). The following web pages can also be consulted for further information: http://www.ulb.ac.be/di (Computer Science Dept. homepage), http://www.ibsquare.be (Interuniversity Institute for Bioinformatics in Brussels), mlg.ulb.ac.be (ULB Machine Learning Research Group)
1 Description of Position :
Candidates are expected to trigger and promote active collaborations within the context of IB2 with molecular, biological and medical research groups at the ULB. They are furthermore expected to lead a high-quality research and teaching program in the specified areas, preferably with a specialization in the analysis of genomic, transcriptomic and/or epigenomic data and the design and deployment of advanced data science (e.g. machine learning, data mining, big data) methods. Significant research and teaching experience, as well as a strong publication record in international journals and/or high impact international conferences are required. The successful candidate will be invited to apply for a grant from the European Research Council (ERC) and for any sources of outside funding (FNRS, Europe, Regional funds, etc…) enabling them to develop their research. The ULB Research Department will assist with applications. As stated by its statutes, the University of Brussels is a non-discriminating institution and all its members are expected to adhere to its fundamental principles.
Description of Scientific and Pedagogical Objectives:
The candidate will take part in teaching activities in the Bachelor and Master programs in Computer Science and the Master in Bioinformatics and Modeling and will participate in the supervision of Master dissertations. The first years she/he will have a reduced teaching charge. After a few years this charge will increase to reach a level comparable to that of her/his colleagues (typically 4 or 5 hours a week for two semesters, plus some supervision of exercise sessions). The ability to strengthen existing research areas at ULB will be considered as an asset, too. The position involves also commitment to administrative tasks. She/ he will furthermore be expected to take an active role in the management and supervision of the research activities in the Interuniversity Institute for Bioinformatics in Brussels (IB2). For any additional information (e.g. concerning courses to be taught or the research carried out in the Department) please see contact details below.
Field of Research :
All applicants need to hold either a PhD in Computer Science, Bioinformatics, Computational Biology, Bioengineering, or related disciplines. Experience in interdisciplinary collaboration as well as significant research stays in foreign universities or research laboratories are important assets.
The teaching duties at the time of hiring will include :
The first years the applicant will be involved in Master-level courses in Bioinformatics and Computational Biology currently organized in the Master in Computer Science and the Master in Bioinformatics and Modeling. For candidates not fluent in French, a temporary period of teaching in English may be granted for teaching at the Master level. After this period (for up to three years) the position will become permanent, requiring that the applicant will also be able to teach in French at the Bachelor level.
2. Teaching duties may be reviewed periodically and are subject to modification over time.
documents attesting to 4 years of teaching and research experience
a report of around 3500 signs on the candidate’s research activities and research project, indicating how the candidate would integrate into ULB research teams
a report of about 3500 signs on the candidate’s previous teaching activities and a project describing their teaching mission during the 5 years following their appointment, that integrates, in a coherent manner, into the vision of the unit in which the candidate will be working and the educational profiles of the programmes on which the candidate will be teaching.
a note on international projects and achievements
please provide full names and email addresses for five referees who may be contacted by the university bodies responsible of evaluating candidate applications. We ask that you be mindful of providing a balanced gender divide between referees and ensure that they have no conflict of interest. Candidates applying for several vacancies are required to send a separate file for each one.
Internal administrative data : Vacancy number : 15/A076 University payroll position : 15-B-CCO-127 (F) (1.00 ETP) Administrative Board reference : CoA. 23/11/15 pt III.02
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: firstname.lastname@example.org.
Please send your CV, motivation letter and contact information for three references, publication list with indication of the citation number of each published paper.
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 (http://ibug.doc.ic.ac.uk/people/orudovic).
Pr. Gianluca Bontempi co-Head of the Machine Learning Group Département d’Informatique Université Libre de Bruxelles Boulevard du Triomphe – CP212 1050 Bruxelles, Belgium email: email@example.com Office Phone: +32-2-650 55 91 Fax: +32 2 650.56.09 mlg.ulb.ac.be
Director Interuniversity Institute of Bioinformatics in Brussels (IB)² ibsquare.be