Post-doc positions at University of Liege, Belgium

The Bioinformatics and Modeling research unit at the GIGA Biomedical Research Center and at the Montefiore Institute of Electrical Engineering and Computer Science of the University of Liège is seeking for Post-Doctoral researchers respectively in machine learning for bioimage informatics and machine learning for biological network inference to begin between October 2013 and January 2014.

Theme 1: Machine learning for bioimage informatics The researcher will be working closely with a team of software developers, researchers in machine learning, and biologists, to advance high-throughput automated analysis of high-resolution images in the context of cancer research, developmental biology, and diagnostic pathology. The applicant will be involved in the design of novel algorithms and their large-scale evaluation for cell and phenotype recognition, and tissue segmentation and quantification. She/He will have access to a high-performance computing environment and the inhouse developed Cytomine platform able to process terabytes of imaging data.

Theme 2: Machine learning for biological network inference The researcher will participate to the effort of the team on the development of machine learning techniques for the inference of biological networks. In particular, the applicant will be involved in the extension of network inference methods to integrate various kinds of data and the practical application of these methods on real biomedical datasets. Depending on the interest of the applicant, the work could focus more on methodological developments in machine learning or on some specific biomedical applications.

Applicants should hold a PhD and have strong knowledge in machine learning,
bioinformatics and/or computer vision. Programming and data analysis
skills are also highly desirable. The candidates should be highly motivated,
with a strong interest in large-scale biomedical applications. A working
knowledge of English language is mandatory, and of French is a plus.

Application procedure: Interested individuals should send a CV, a brief
statement of research and development interests, three relevant publications,
and the names and contact details of two references by e-mail to:
Raphaël Marée ( with subject “Postdoc ULG”.
Candidates interested should send their application before
mid-February 2013. The final decision will be taken in June 2013. The
position will be available for an initial period of 1 year, with
possible one-year extension after mid-term evaluation.

More information:
– The GIGA research center:
– The Montefiore Institute:
– Research Unit in Systems and Modeling:
– The CYTOMINE research project: (Theme 1)
– The Liège city:

Research positions in computer vision at Xerox

The Textual and Visual Pattern Analysis group of the Xerox Research Centre Europe (XRCE) is looking for two researchers in the field of computer vision. The successful candidates will contribute – in collaboration with the rest of the team – to the invention, development and benchmarking of computer vision technologies such as image classification, image retrieval, object localization, etc. in both images and videos. The potential areas of application of the developed technology will include transportation (e.g. tracking, counting and classifying vehicles) and retail (e.g. detection and classification of products on shelves).
• Ph.D. degree in computer vision or machine learning.
• Excellent publication record in major computer vision / machine learning / multimedia conferences and journals.
• Strong development skills, preferably in C/C++.
• Fluent in written and oral English.
• Highly motivated.
Team and center: The Textual and Visual Pattern Analysis group specializes in understanding, organizing, retrieving and enhancing visual and hybrid content. We have extensive experience and state-of-the-art systems in image categorization, image retrieval, image enhancement, quality / aesthetic assessment and document image processing. Our technology has won numerous awards in public competitions such as the PASCAL Visual Object Challenge, ImageCLEF or the ImageNet Large Scale Visual Recognition Challenge.
The Xerox Research Centre Europe is located in Grenoble, in the heart of the French Alps, close to both the Italian and Swiss borders. The centre is part of the global Xerox Innovation Group made up of 650 researchers and engineers in five world renowned research and technology centers.

Starting Date: asap.
Duration: the positions are 12 months post-doc positions. However, we might consider permanent positions for exceptional candidates.
Application instructions: please send your CV, cover letter as well as the name of at least one reference to both and

PhD/Post Doc in the area of speech recognition and natural language understanding at Saarland University

PhD/Post Doc in the area
speech recognition and natural language understanding
at Saarland University

Present speech recognition systems are unaware of the environment in which they run. Contextual information from the environment can be integrated in the recognition process to reduce word error rate and concept error rate. For the specific task at hand, we will focus on controller-pilot communication in cooperation with the German Aerospace Center (DLR), which will provide realistic data with dynamic context. The task is to perform research on methods for integrating the contextual knowledge into the speech recognizer.

The successful candidate should have a degree in computer science, electrical engineering, computational linguistics or a closely related area. Excellent programming skills are important. A good math background is a plus. Very good oral and written communication skills in English will be valued.

Saarland University is one of the leading European research sites in computational linguistics and offers an active, stimulating research environment. Close working relationships are maintained between the Departments of Computational Linguistics and Computer Science. Both are part of the Cluster of Excellence, which also includes the Max Planck Institutes for Informatics (MPI-INF) and Software Systems (MPI-SWS) and the German Research Center for Artificial Intelligence (DFKI).

The position is suitable for a PhD student or a Post Doctoral researcher. The salary will be in the range of 33,000 Euros to 51,000 Euros per year depending on the qualification and professional experience of the successful candidate. Earliest possible starting date is February 1st. The position is for two years with the plan to extend it.

Each application should include:

* Curriculum Vitae including a list of publications
(if applicable)
* Transcript of records
* Short statement of interest (not more than half a
* Names of two references
* Any other supporting information or documents

Applications (documents in PDF format in a single file) should be sent no later than , Friday January 18th to:

Further inquiries regarding the project should be directed to:

13 Early-Stage Researcher Fellowships (PhD positions) in Marie Curie Initial Training Network for “Machine Learning for Personalized Medicine”

Call for Applications:

13 Early-Stage Researcher Fellowships (PhD positions) are available in a newly established Marie Curie Initial Training Network for “Machine Learning for Personalized Medicine” (MLPM) in 2013.

All details and application instructions can be found on the European Commission’s Job Platform EURAXESS:

MSR PhD studentship available at Edinburgh

We are seeking to award a Microsoft PhD Scholarship on the topic of approximate Bayesian inference for data pipelines.

The PhD scholarship is fully funded for three years. The project will be supervised by Dr Iain Murray of the University of Edinburgh, in collaboration with Dr John Winn at Microsoft Research Cambridge.

Deadline: 1 March 2013, with first consideration, 28 January 2013.

For full information, see

PhD Studentship Fully Funded – Centre for Vision, Speech and Signal Processing, University of Surrey, UK

Real-time 3D Computer Vision for Film Production
Stipend £14,000/annum (tax-free) + Home/EU Fees
A fully funded PhD studentship is available for research into 3D computer vision to support film production. Research will be conducted as part of a collaborative project with two leading UK companies in the film industry and provide opportunities to gain industry experience.

Further details:

Closing date for applications: 31st January 2013

ECML/PKDD 2013 calls for journals, conference, tutorial and workshop proposals

– Important: ECML PKDD 2013 will have a continuous journal submission track in addition to the regular conference submission. The journal submission track is already open. —

European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases
Prague, Czech Republic, September 23 to 27.

The call for the journals and the conference can be found online here:
The call for workshop proposals can be found here:
The call for tutorial proposals can be found here:

Tutorial proposal deadline: Friday, March 8, 2013
Tutorial acceptance notification: Friday, March 29, 2013

The following deadlines are important for the workshop organizers:
• Workshop proposal deadline: Friday, March 8, 2013
• Workshop acceptance notification: Friday, March 29, 2013
• Workshop websites and call for papers online: Friday, April 5, 2013
• Workshop proceedings (camera-ready): Friday August 9, 2013
Journal track:
• bi-weekly batch deadlines on Sundays (GMT). The remaining deadlines are 6.1., 20.1., 3.2., 17.2. and 3.3. in 2013.
• aiming for notification within 8 weeks (for submissions within the page restrictions)
Proceedings track:
• abstract submission: Thursday, April 18, 2013

• paper submission: Monday, April 22, 2013
• notification: Friday, June 14, 2013
• camera ready copy: Friday, June 28, 2013


Postdoctoral Position in Machine Learning and Bioinformatics University of Bristol, United Kingdom

We are seeking to appoint an outstanding postdoctoral researcher, interested in machine learning and bioinformatics, for a 3 year fixed term contract position. Based in the Intelligent Systems Laboratory, University of Bristol, United Kingdom, you will be interested in the development and application of machine learning methods to the interpretation of biomedical datasets.
Within this project we will devise novel and use established methods from modern machine learning including Bayesian techniques and probabilistic graphical methods, kernel-based methods and other approaches. We are keen to develop active learning approaches in which bioinformatics methods are used to infer maximally informative biological experiments with the results in turn used to improve a hypothesis. Algorithm development will be pursued with Dr. Colin Campbell of the Intelligent Systems Laboratory. Our main collaborators on the biological side are Prof. David Murphy and Dr. Charlie Hindmarch of the Henry Wellcome Laboratories for Integrative Neuroscience, University of Bristol, who have an interest in understanding the hypertensive state in humans. Apart from using bioinformatics methods to highlight the role of particular genes in this condition, they are interested in understanding and mapping regulatory pathways.
Thus, the candidate may also have some interest in network inference, both using unsupervised and supervised methods.
Eligible candidates should ideally have a background in machine learning, statistics or bioinformatics and should have excellent mathematical and computational skills.

This post is hosted within the Intelligent Systems Laboratory (the ISL) of the University of Bristol. The ISL has 16 staff members and about
50 postdoctoral researchers and research students and pursues a broad programme of research across machine learning and related disciplines.

Informal enquiries can be made to Dr Colin Campbell:
Tel: +44 (0)117-33-15620

The successful applicant for this vacancy may be appointed either on a fixed term or a permanent contract depending on the extent of their previous relevant research experience, in line with the University’s Fixed Term Contract Agreement. Further information can be found at

Job number: ACAD100154
Division/School: Merchant Venturers’ School of Engineering Contract type: Fixed-term contract staff Working pattern: Full time
Salary: £34223 – £38522
Funder: EPSRC
Closing date for applications: 20-Jan-2013

Full details are at:
using job number reference: ACAD100154

and direct link:

Assistant Professor in Statistics and Probability University of Groningen the Netherlands

Faculty of Mathematics and Natural Sciences

Tenure track assistant professor in Statistics (deadline 1 March, 2013)

The Faculty of Mathematics and Natural Sciences has a vacancy for a tenure track assistant
professor in Statistics in the Johann Bernoulli Institute for Mathematics and Computing Science
(JBI). The candidate is expected to initiate new research in statistics on the interface between
substantial applications and mathematical statistics. He/she has to attract new PhD projects and
build up a leading international position in this field. He/she is an excellent teacher who can
motivate students of different disciplines and he/she has to develop new courses on specific topics
about this subject in the BSc and the MSc programmes. Teaching duties include the supervision of
bachelor, master and PhD students.

The candidate should have a thorough knowledge of Mathematical Statistics, Applied
Statistics and Stochastic Modelling. He/she has international experience (postdoctoral) and a track
record of outstanding research and is internationally recognized, with publications in leading
journals cited by prominent researchers. He/she has excellent organisational and teaching skills, is
fluent in English (as all teaching is done in English). The candidate should also have two year of
post-doctoral experience.

Details can be found on:
Additional Information

Further, more detailed information can be obtained from Prof. dr. E.C. Wit, chair of the Statistics
and Probability Unit (tel + 31 (0)50 3635170, email ).
About position: http ://
About the Statistics unit:

The deadline for this position is 1 March 2013.
Interested candidates are requested to submit
1. letter of motivation, including a statement on teaching goals and experience, and a brief
description of scientific interests (maximum: 3 pages).
2. CV, including 5 references, a list of publications, a list of five self-selected “best papers”).
Via website:

SIMBAD 2013 (Similarity-Based Pattern Analysis and Recognition), York, UK



2nd International Workshop on Similarity-Based Pattern Analysis and Recognition

July 3-5, 2013
York, UK


Traditional pattern recognition techniques are intimately linked to the notion of “feature space.” Adopting this view, each object is described in terms of a vector of numerical attributes and is therefore mapped to a point in a Euclidean (geometric) vector space so that the distances between the points reflect the observed (dis)similarities between the respective objects. This kind of representation is attractive because geometric spaces offer powerful analytical as well as computational tools that are simply not available in other representations. However, the geometric approach suffers from a major intrinsic limitation, which concerns the representational power of vectorial, feature-based descriptions. In fact, there are numerous application domains where either it is not possible to find satisfactory features or they are inefficient for learning purposes.

In the last few years, interest around purely similarity-based techniques has grown considerably. For example, within the supervised learning paradigm the well-established kernel-based methods shift the focus from the choice of an appropriate set of features to the choice of a suitable kernel, which is related to object similarities.
However, this shift of focus is only partial, as the classical interpretation of the notion of a kernel is that it provides an implicit transformation of the feature space rather than a purely similarity-based representation. Similarly, in the unsupervised domain, there has been an increasing interest around pairwise or even multiway algorithms, such as spectral and graph-theoretic clustering methods, which avoid the use of features altogether.

By departing from vector-space representations one is confronted with the challenging problem of dealing with (dis)similarities that do not necessarily possess the Euclidean behavior or not even obey the requirements of a metric. The lack of such properties undermines the very foundations of traditional pattern recognition theories and algorithms, and poses totally new theoretical/computational questions and challenges.

The aim of this workshop, which follows the one held in Venice in 2011 (, is to consolidate research efforts in this area, and to provide an informal discussion forum for researchers and practitioners interested in this important yet diverse subject. We aim at covering a wide range of problems and perspectives, from supervised to unsupervised learning, from generative to discriminative models, and from theoretical issues to real-world applications.

Original, unpublished papers dealing with these issues are solicited.
Topics of interest include (but are not limited to):

– Embedding and embeddability
– Graph spectra and spectral geometry
– Indefinite and structural kernels
– Game-theoretic models of pattern recognition
– Characterization of non-(geo)metric behavior
– Foundational issues
– Measures of (geo)metric violations
– Learning and combining similarities
– Multiple-instance learning
– Applications


All papers (not exceeding 16 pages) must be submitted electronically at the conference website (
All submissions will be subject to a rigorous peer-review process.
Accepted papers will appear in the workshop proceedings, which will be published in Springer’s Lecture Notes in Computer Science (LNCS) series.

In addition to regular, original contributions, we also solicit papers (in any LaTeX format, no page restriction) that have been recently published elsewhere. These papers will undergo the same review process as regular ones: if accepted, they will be presented at the workshop but will not be published in the workshop proceedings.

Submission implies the willingness of at least one of the authors to register and present the paper, if accepted.


Avrim Blum, Carnegie Mellon University, USA Nello Cristianini, University of Bristol, UK Frank Nielsen, Sony Computer Science Laboratories Inc, Japan


Paper submission: February 1, 2013
Notifications: March 15, 2013
Camera-ready due: April 25, 2013
Workshop: July 3-5, 2013


Program Chairs
Edwin Hancock, University of York, UK
Marcello Pelillo, University of Venice, Italy

Steering Committee
Joachim Buhmann, ETH Zurich, Switzerland
Robert Duin, Delft University of Technology, The Netherlands
Mario Figueiredo, Technical University of Lisbon, Portugal
Edwin Hancock, University of York, UK
Vittorio Murino, Italian Institute of Technology, Italy
Marcello Pelillo (chair), University of Venice, Italy

Program Committee
Maria-Florina Balcan, Georgia Institute of Technology, USA
Manuele Bicego, University of Verona, Italy
Avrim Blum, Carnegie Mellon University, USA
Joachim Buhmann, ETH Zurich, Switzerland
Terry Caelli, NICTA, Australia
Tiberio Caetano, NICTA, Australia
Umberto Castellani, University of Verona, Italy
Luca Cazzanti, University of Washington, Seattle, USA
Nello Cristianini, University of Bristol, UK
Robert Duin, Delft University of Technology, The Netherlands
Aykut Erdem, Hacettepe University, Ankara, Turkey
Francisco Escolano, University of Alicante, Spain
Mario Figueiredo, Technical University of Lisbon, Portugal
Ana Fred, Technical University of Lisbon, Portugal
Mehmet Gonen, Aalto University School of Science, Finland
Marco Gori, University of Siena, Italy
Bernard Haasdonk, Universitaet Stuttgart, Germany
Edwin Hancock, University of York, UK
Robert Krauthgamer, Weizmann Institute of Science, Israel
Marco Loog, Delft University of Technology, The Netherlands
Marina Meila, University of Washington, Seattle, USA
Vittorio Murino, Italian Institute of Technology, Italy
Marcello Pelillo, University of Venice, Italy
Massimiliano Pontil, University College London, UK
Antonio Robles-Kelly, NICTA, Australia
Fabio Roli, University of Cagliari, Italy
Samuel Rota Bulo’, University of Venice, Italy
Volker Roth, University of Basel, Switzerland
John Shawe-Taylor, University College London, UK
Andrea Torsello, University of Venice, Italy
Richard Wilson, University of York, UK
Lior Wolf, Tel Aviv University, Israel