PASCAL VOC 2009 test data available

We are pleased to announce that the test data for the PASCAL VOC 2009 challenge is now available. Please see the web page for details:

http://pascallin.ecs.soton.ac.uk/challenges/VOC/voc2009/#testdata

A reminder of the challenge timetable:

* 15 May 2009: Development kit (training and validation data plus
evaluation software) made available.

* 15 June 2009: Test set made available.

* 7 September 2009. Deadline for submission of results.

* 3 October 2009: Workshop in association with ICCV 2009, Kyoto, Japan.

Mark Everingham
Luc Van Gool
Chris Williams
John Winn
Andrew Zisserman

Postdoctoral position in Machine Learning/Computational Biology in Tübingen, Germany

Machine Learning in Biology Group on the Max Planck Campus
Tuebingen, Germany *

Group Description
The Max Planck research group “Machine Learning in Biology” led by Gunnar Raetsch has a postdoctoral position available. We are situated in the Friedrich Miescher Laboratory in Tübingen, Germany, which is part of an excellent research campus including the Max Planck Institutes for Developmental Biology and Biological Cybernetics and the University of Tübingen. Our ongoing projects are related to the development of large-scale and interpretable learning methods for computational transcriptome analysis, gene finding, understanding transcriptional and post-transcriptional regulation, and the analysis of polymorphisms (cf. http://www.fml.mpg.de/raetsch/research).

Position Requirements
We are looking for an enthusiastic candidate who is interested in applying and/or developing machine learning or related data analysis techniques to relevant problems appearing in genome biology. Possible topics include large scale learning methods for classification and structured output prediction to analyze the regulation of RNA processing, epigenetics of post-transcriptional regulation, dynamical modeling of biological systems, and genome-wide association studies. There will be many possibilities to collaborate with others in the group and on campus and lots of freedom to pursue own ideas.

The candidate should have a Ph.D. (in computer science, statistics, biostatistics, computational biology, or a related field) with a strong publication record and strong professional references. The
ideal candidate should have demonstrated interests and experience in the analysis of genomic data; strong knowledge of molecular biology; extensive programming experience pertinent to the analysis of large and diverse datasets; multi-disciplinary team working capabilities. Excellent communication skills are required for effective interaction with group members and collaborators.

Application Procedure
Interested applicants should submit a CV, a cover letter stating qualifications as well as research interests, and letters of reference via the online submission system available at http://jobs.tuebingen.mpg.de/ag-raetsch. Please feel free to also contact Gunnar Raetsch (Gunnar.Raetsch (at) tuebingen.mpg.de) informally by email or at ISMB 2009 in Stockholm if you have any questions.

Machine Learning opportunity with Nokia

Software Engineer, Machine Learning

Description
Nokia Maps, is looking for excellent Software Engineers with a background in Machine Learning and/or Information Retrieval. We are filling positions in this area both at the PhD-level (Senior Software Engineer) and on the M.Sc.-level (Software Engineer).

Nokia Maps comes preinstalled on more phones than any other maps software in the world, including more than 30 million GPS-enabled Nokia phones sold in 2008 alone. From its inception, Nokia Maps was designed with mobile in mind, requiring very little bandwidth and even supporting offline use of maps.

As a Software Engineer in Machine Learning you will design and implement algorithms that enable new cutting-edge product features within Nokia Maps/Location Based Services. You bring with you hands-on experience in implementing algorithms for multivariate data analysis including clustering, modeling/parameter estimation, prediction, etc. You are responsible for the entire data analysis cycle from initial visualizations to identifying modeling alternatives and trade-offs to rigorous benchmarking. You have worked on large, challenging data sets before (e.g. in bioinformatics, search and discovery, computer vision, etc.) and you are serious about algorithm efficiency and parallelization.

Our offices are located in the heart of Europe, the workplace is extremely international and the working language is English.

Qualifications
-A degree in Computer Science/Statistics/Physics/Mathematics, M.Sc. or PhD (senior positions)
-In-depth knowledge and 6+ years of experience in practical Machine Learning/Data Analysis and/or Information Retrieval
-Strong Java/J2EE and/or C/C++ coding skills, and a track-record in software development
-Experience in the domain of text/web data and/or context data is a plus
-Team player by nature, self-driven, pragmatic
-To flourish in our international environment, you will need to be fluent in spoken and written English

Please contact Robert Rees (R.Rees (at) vertex-solutions.co.uk) for more information.

Call for Participation: ECML PKDD 2009 – early registration deadline approaching!

The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD) will take place in Bled, Slovenia, from September 7th to 11th, 2009. This event builds upon a very successful series of 19 ECML and 12 PKDD conferences, which have been jointly organized for the past eight years. It has become the major European scientific event in these fields and in 2009 it will comprise presentations of contributed papers and invited speakers, a wide program of workshops and tutorials, a discovery challenge, a demo track and an industrial track.

http://www.ecmlpkdd2009.net/attending/registration/

Early registration Until July 5th
Regular – 340 EUR
Student – 290 EUR
Student (banquet not incl.) – 220 EUR

Registration until August 31st
Regular – 430 EUR
Student – 380 EUR
Student (banquet not incl.) – 310 EUR

Late registration
Regular – 520 EUR
Student – 470 EUR
Student (banquet not incl.) – 400 EUR

Note that this year the conference proceedings are not included in the registration fee, but you have a possibility to order Springer books or USB memory keys. Registered participants can also buy extra tickets for social events for accompanying persons (for individual events or one ticket to all events for a discounted price). T-shirts are included in the conference fee so we kindly ask you to mark your size on the registration form. This way we will be able to provide enough T-shirts in different sizes.

Morpho Challenge 2009: Call for participation

Please be reminded about the Morpho Challenge 2009 competition which
is part of the PASCAL Challenge Program.

The rules (briefly):
1. Prepare morpheme analysis for the provided word lists
2. The organizers will run evaluations in various tasks and languages
DL for submissions is 1 Aug, 2009.

The Morpho Challenge results workshop will be held in conjunction with
CLEF 2009 (Cross-Language Evaluation Forum) which takes place from 30
September to 2 October in Corfu, Greece.
DL for the papers is extended to 15 Aug, 2009.

More info: http://www.cis.hut.fi/morphochallenge2009/

Please contact, if you would like to be added in our mailing list.

Mikko Kurimo, Sami Virpioja and Ville Turunen
Adaptive Informatics Research Centre, Helsinki University of Technology
The organizers

Invitation to Project Exhibition at international conference ECML PKDD 2009

ECML PKDD 2009 (http://www.ecmlpkdd2009.net/) invites all interested researchers to actively participate in the Project Exhibition presenting posters/demos on their projects.

The goal of the exhibition is mainly networking and exchanging of the results/experience. We would like to help in disseminating the results of different projects related to machine learning and knowledge discovery applications and technologies. We will have boards for hanging posters, but you may additionally bring your notebook to show demos, …

If interested please respond by 16th of August to blaz.fortuna (at) ijs.si by sending the name of your institution/group and a 2-page description of the project you would like to present at the exhibition describing how machine learning and/or knowledge discovery technologies are used in the project. The selected project proposals will be presented at the ECML PKDD Poster Reception on Tuesday, 8th Sept. 2009.

Tentative program:
Monday, 7th
14:00 – 15:30 Invited speaker from EC
15:30 – 16:00 Coffee break
16:00 – 17:30 Poster highlights (5 minutes each)
Tuesday, 8th
Poster session (embedded in poster reception)

We are looking forward to hearing more about your work at the exhibition.
Blaz Fortuna and Dunja Mladenic

Research Scientist Position at Xerox Research Centre Europe

Position: Research Scientist in Text Mining and Social Networks

XRCE’s Textual and Visual Pattern Analysis (TVPA) area is an expanding team, which specializes in text and visual content understanding. Our mission is the delivery of Xerox’s innovative solutions that make everyday interaction with visual and textual content simple and effective.
TVPA is involved in several French and European Community Projects aimed at developing the next generation of multimodal information access systems exploiting recent advances in Machine Learning, Computational Linguistics and Social Network Analysis. In this framework, the TVPA group is looking for a Research Scientist with the following ideal profile:

Profile:

* Ph.D in Mathematics (Statistics), Natural Language Processing or Computer Science
* Strong skills in text mining, machine learning, statistics, social networks, hyper-graph analysis, data stream clustering and tensor analysis.
* A good command of English written and oral communication skills is required, as well as open-mindedness and the will to collaborate with a team.

The successful candidate will be in charge of:

1. Designing and implementing original clustering methods for textual streams.
2. Designing and implementing social network-based algorithms for collaborative document management, including categorization, clustering, retrieval, semi-automatic generation, sharing and co-editing, meta-tagging and trust analysis.
3. Investigating and developing tensor-based decomposition methods to analyze hyper-networks.
4. Collaborating with other project partners in order to integrate the research results in a common environment/platform (sharing components, algorithms and methods).

All these activities will be conducted in close collaboration with other members of the team. As a researcher in TVPA you will also be expected to generate and follow up on new ideas, build strong competencies and intellectual property on your field of research and be an active member of the scientific community participating in key conferences and collaborating with external teams.
Inquiries can be sent to Jean-Michel.Renders at xrce.xerox.com

Application deadline: July 31st, 2009
Starting date: September, 2009
Type of contract: Temporary position – 18 months
To apply: Please send your CV and cover letter to: xrce-candidates (at) xrce.xerox.com.

Xerox Research Centre Europe (XRCE) is a young, dynamic research organization, which creates innovative new business opportunities for Xerox in the digital and Internet markets. XRCE is a multicultural and multidisciplinary organization set in Grenoble, France. We have renowned expertise in natural language processing, work practice studies, image processing and document structure. The variety of both cultures and disciplines at XRCE makes it both an interesting and stimulating environment to work in, leading to often unexpected discoveries! XRCE is part of the Xerox Innovation Group made up of 800 researchers and engineers in four world-renowned research and technology centres.

Post doctoral position in Machine Learning/Cognitive Vision/CBIR

http://institute.unileoben.ac.at/infotech/research/jobs/nfn-position-2009-06.html

For a project funded by the Austrian Science Foundation (FWF) and the European Commission, we are looking for a highly motivated post doctoral researcher with background in machine learning and/or cognitive vision and/or content based image retrieval. Among the possible fields of specialization are on-line learning, active learning, reinforcement learning, visual object classification, relevance feedback, and query-by-example search.

To learn more about the above project and the research at the Chair of Information Technology, University of Leoben, Austria, please visit http://institute.unileoben.ac.at/infotech.

This position will be filled as soon as possible for the duration of 12 month (with a possible extension). Depending on your qualification salary is 30000-45000 EUR per year (after paying all social and insurance benefits and taxes this is net 1500-2000 EUR per month). Highly qualified PhD candidates may be considered as well.

Applicants should submit 1) a CV, including a brief research statement, 2) 1-3 recent publications in electronic format, and 3) the names and contact information of three individuals who can serve as references.

Contact:
Univ.-Prof. Dr. Peter Auer
University of Leoben
Chair for Information Technology
Franz-Josef-Strasse 18, A-8700 Leoben, Austria
Fax: +43(3842)402-1502
E-mail: auer (at) unileoben.ac.at

PASCAL2 Workshop on Spatiotemporal Modelling

http://homepages.inf.ed.ac.uk/mdewar1/workshops/spatiotemporal/

12th – 14th October 2009
Informatics Forum, Edinburgh, UK

Submission Deadline: July 30th 2009

CALL FOR PAPERS

Recent years have witnessed a considerable amount of research on modelling spatio-temporal systems both in an engineering and scientific domain. The combination of novel theoretical problems, important applications areas and mix of disciplines in spatiotemporal modelling offers real potential for some intellectual excitement.

The workshop aims to bring together the various interested communities (machine learning, control, statistics, geosciences, econometrics, ecology etc.), to focus on theoretical aspects of spatiotemporal modelling and to encourage cross pollination of ideas.

The workshop will be a two-day , single-track workshop, with two half days and one full day in between. We have 6 invited speakers and would like to encourage submission of abstracts for additional talks and posters. The oral sessions will be relatively short, punctuated by breaks and poster sessions to encourage discussion. We hope that submissions will come from a range of topics and applications surrounding spatiotemporal modelling, for example:
* learning and inference
* multi-scale modelling
* experiment design
* spatiotemporal covariance functions
* heterogeneous models
* sensor networks
* disease mapping
* …

KEY SPEAKERS

* Manfred Opper, AI, Berlin.
* Sujit Sahu, Mathematics, Southampton.
* John Haslett, Statistics, Trinity College Dublin.
* Chris Glasbey, Biomathematics & Statistics Scotland, Edinburgh.
* Geir Storvik, Mathematics, Oslo.
* (and hopefully) Dan Cornford, Computer Science, Aston.

IMPORTANT DATES

* Submission Deadline: August 14th 2009
* Author Notification: August 31st 2009
* Workshop: 12th – 14th October 2009

PAPER SUBMISSION

We welcome submissions of one page abstracts, in the Springer LNCS style. You can submit abstracts here:
http://homepages.inf.ed.ac.uk/mdewar1/workshops/spatiotemporal/submission.html

ORGANISERS

* Dr Michael Dewar
* Prof Chris Glasbey
* Prof Chris Williams
* Dr Amos Storkey
* Dr Guido Sanguinetti
* Prof Visakan Kadirkamanathan

Funded PhD position in machine learning at the University of Technology of Compiègne (France)

The Laboratory Heudiasyc, CNRS & University of Technology of Compiègne (France) invites applications for a fully funded 3-years PhD position.

Topic: “Model Selection in Block-Clustering”

Starting date: October 2009

Block clustering aims at partitioning simultaneously the rows and columns of a data matrix. This problem, which has been investigated from the early 80’s in data analysis, has recently attracted interest in the machine learning community, thanks to applications such that text mining, marketing or recommender systems (see e.g. Netflix challenge). This thesis aims at developing new model selection tools for block clustering, starting from their theoretical foundations, up to their empirical evaluation. It will be developed in the ClasSel project funded by the French National Research Agency.

Clustering, and particularly block-clustering is highly contingent on the choices of the fitting criterion and the number of classes. Viewing the clustering problem as a density estimation problem provides answers to these problems thanks to the general-purpose estimation and model selection tools developed in the statistical framework. In this context, model selection is usually performed via penalized maximum likelihood scores, that trade-off fitting for model complexity. The main approaches are AIC (Akaike Information criterion) that builds on Kullback-Leibler divergence and BIC (Bayesian Information criterion) that maximizes the model posterior. However, these criteria do not take into account the classification objectives when density models are used in the clustering framework. A third criterion, ICL (Integrated Completed Likelihood) accounts for this aspect. Finally, resampling methods, though scarcely used in clustering, may also provide estimates of the optimism of complex models.

All these criteria are sample-size dependent. Hence, their adaptation to block-clustering is problematic since problem size is characterized here by the number of rows and the number of columns of the data matrix. The notion of sample size cannot be transposed directly, and the first attempts to apply information criteria in this framework are not convincing. This project aims at proposing such criteria, either by revising the standard criterion, or by starting from new theoretical grounds.

Applicants should complete their Master degree in 2009, and have interest and expertise in machine learning, statistics, computer science and/or applied mathematics.

Expressions of interest with a short CV, including reference(s) should be sent to: Gerard.Govaert (at) utc.fr or Yves.Grandvalet (at) utc.fr

Some links:
– Heudiasyc Lab. http://www2.hds.utc.fr/index.php?id=1&L=1
– University of Technology of Compiègne http://www.utc.fr/the_university/index.php
– Compiègne is a small town with 70’000 inhabitants, at a 45mn commute of Paris, see http://en.wikipedia.org/wiki/Compi%C3%A8gne