PostDoc Position on Biomedical Image Analysis with Machine Learning Methods

The group of Computational Neuroscience and Machine Learning at the Frankfurt Institute
for Advanced Studies (FIAS) and the group of Applied Systems Biology at the Leibniz
Institute for Natural Product Research and Infection Biology in Jena offer a PostDoc
position for research on Machine Learning approaches to the analysis of microscopy images
on infection processes.

The interdisciplinary project aims at using modern probabilistic approaches to autonomously
learn representations of cells and their interactions in microscopy images. The representations
will be used to automatically analyze the complex interplay between pathogens and immune
cells during infection. The technology learned during the project is based on Bayesian
generative models that can be applied to a large range of fields and offers the candidate
numerous perspectives for the future.

Applicants should have a doctoral degree in Machine Learning, Physics, Computer Science,
Mathematics, Electrical Engineering, or a related field. Strong analytical skills and good
programming experiences are required. Experience in the analysis of data and the use of
Machine Learning approaches is highly desirable. Good communication skills in English are essential.

The offered position is a fully funded research position and we are looking for a highly
qualified candidate. The PostDoc will work in international and young research groups at
Frankfurt and Jena. We aim at high-profile research, publish in leading journals and
conferences of the field, and offer and encourage collaborations with leading international
research groups.

Please send applications by

March 7, 2010,

to Johanna Dilley including:

* complete scientific curriculum vitae (including a list of publications, if applicable)
* copies of certificates
* short statement of research interests and achievements (half a page)
* two letters of reference or the names and contact details of two individuals who are willing
to write a recommendation letter if contacted
* if applicable, provide a proof of proficiency in English (e.g., TOEFL, IELTS, or similar)

Applications received after March 7 may not be considered.

After the submission deadline, the position can be filled as soon as a suitable candidate is
found.

For further information about the Computational Neuroscience and Machine Learning group
at the FIAS see:
http://fias.uni-frankfurt.de/cnml

For further information about the Applied Systems Biology group at the Leibniz Institute for
Natural Product Research and Infection Biology see:
http://www.sysbio.hki-jena.de/

Workshop on learning theory in Paris, May 9-11, 2011

On behalf of the French Mathematical Society, we are happy to announce the following meeting in Paris:

Statistical Learning Theory – “Etats de la Recherche”

Institut Henri Poincaré, Paris
May 9-10-11, 2011

http://learningtheory.state.free.fr/

Scientific committee

Vladimir Koltchinskii (GeorgiaTech)
Gabor Lugosi (Universitat Pompeu Fabra)
Pascal Massart (Université Paris-Sud)
Alain Pajor (Université Paris-Est)

Organizers

Stéphane Boucheron (Université Denis-Diderot)
Nicolas Vayatis (ENS Cachan)

Programme:

A. Mini-courses by:

* Peter Bartlett (UC Berkeley) : Design and theoretical analysis of prediction methods
* Sanjoy DasGupta (UC San Diego) : Unsupervised and minimally-supervised learning.
* Shahar Mendelson (Technion and Australian National University) : Geometric methods in learning theory.

B. Talks by:

Francis Bach (INRIA & ENS Ulm)
Gilles Blanchard (Potsdam University)
Nicolas Broutin (INRIA)
Stéphan Clémençon (Telecom ParisTech)
Stéphane Mallat (Ecole Polytechnique)
Richard Nickl (Cambridge University)
Jean-Luc Starck (CEA)
Gilles Stoltz (ENS Ulm & HEC)
Alexandre Tsybakov (ENSAE ParisTech)

Purpose

The aim of this event is to introduce learning theory to non-experts mathematicians. The participation of junior researchers and graduate students is particularly encouraged.

Registration

Registration is free but mandatory. A limited number of invitations will be delivered. If you are interested in this event, please fill the application form:

http://learningtheory.state.free.fr/index.php?option=com_wrapper&view=wrapper&Itemid=32&lang=fr

For more information

Please check the webpage: http://learningtheory.state.free.fr/.

PhD Scholarship, Heidelberg University

PhD scholarship in the Graduate Program “Semantic Processing” jointly
organized by the Computational Linguistics Department at Heidelberg
University and the NLP Group at HITS gGmbH, Heidelberg, Germany
(March 15th, 2011)

One PhD scholarship (salary EUR 1280/month, tax-free) is available for
a student working in the area of Computational Linguistics/Natural
Language Processing. Candidates are free to choose the topic of their
PhD projects as long as they are within the general interests of the
faculty of the graduate program:
* Anette Frank: statistical semantics, discourse, information extraction
* Sebastian Padó: multilingual NLP, computational psycholinguistics
* Stefan Riezler: statistical machine translation, machine learning
* Michael Strube: discourse, generation, knowledge extraction
The scholarship will be granted initially for two years with the
possibility for a one year extension after successful evaluation.

Candidates should have a strong background in computational
linguistics and possess a Masters or a Diploma degree in either
Computational Linguistics or Computer Science/Linguistics with a
specialization in Natural Language Processing. Experience with machine
learning, corpus-based methods and statistics is a plus. We expect
strong programming skills (Java, C++, or Python).

The graduate program “Semantic Processing”
(http://semproc.cl.uni-heidelberg.de) is jointly organized by the
Computational Linguistics Department at the University of Heidelberg
(http://www.cl.uni-heidelberg.de) and the NLP Group at HITS gGmbH
(http://www.h-its.org/nlp). Members of the graduate program
participate in a PhD seminar series and may attend lectures at the
university. The graduate program provides a lively research
environment in a group of PhD students. We encourage interdisciplinary
research activities with Computer Science, Linguistics, Psychology,
Geography and other disciplines.

To apply, please send your CV, a statement of research, a copy of your
degree certificate, and a study transcript before March 15th, 2011 to:

Anke Sopka
Institut für Computerlinguistik
Universität Heidelberg
Im Neuenheimer Feld 325
69120 Heidelberg
Germany

Email: icl(at)cl.uni-heidelberg.de
Tel.: +49 6221 54-3245

PhD Position In Venice

Applications are invited for one PhD position in Computer Science at Ca’ Foscari University, Venice, Italy (http://www.unive.it) to undertake research in the areas of computer vision and pattern recognition on:

Similarity, clustering and matching of relational structures.

The activitiy will be closely related to the themes of the EU FP7 SIMBAD project (http://simbad-fp7.eu).

The position is funded by the Italian Ministry of University and Research (MIUR) under the “Youth support Fund” program.

The successful candidate will join the Computer Vision and Pattern Recognition Group headed by Prof. Marcello Pelillo, which is a member of the PASCAL 2 Network of Excellence. The group’s research activity is focused primarily on graph-theoretic, optimization, and game-theoretic approaches, and in the interplay between continuous and combinatorial methods. The research spans a range of topics including grouping and segmentation, shape analysis and object recognition, structural matching and learning, and contextual pattern recognition.

For further information and how to apply, please see:
http://www.unive.it/nqcontent.cfm?a_id=82531

Deadline for applications is: ***22 March 2011***

Note: in order to apply for this position, please mention explicitly in the application form the “Youth support Fund” scholarship bounded to the topic “Similarity, matching and clustering of relational structures” – Strategic programme: “ICT and electronic components;” (code 27-05)

Please feel free to contact Prof Marcello Pelillo for further information.
http://www.dsi.unive.it/~pelillo

CFP: META-NET Workshop on “Context in MT”, 14 June 2011

Call for abstracts and participation:

CONTEXT IN MACHINE TRANSLATION
META-NET workshop in ICANN 2011 conference
Espoo, Finland, 14th of June, 2011
Abstract submission: 16th of March, 2011

=== BACKGROUND: ICANN CONFERENCE ===

ICANN 2011 conference brings together researchers from computational
modeling, including machine learning and neural networks as well as
different scientific disciplines in which these methods are applied.
In the ICANN 2011 conference, there will be six keynotes by
renowned scientists:

– Tom Griffiths, University of California Berkeley,
– Riitta Hari, Aalto University,
– Geoffrey Hinton, University of Toronto,
– Aapo Hyvärinen, University of Helsinki,
– John Shawe-Taylor, University College London, and
– Josh Tenenbaum, Massachusetts Institute of Technology.

=== MACHINE TRANSLATION RESEARCH AND CONTEXT ===

Machine Translation can be considered to be one of the most
challenging tasks computer science has ever taken. Statistical methods
have been increasingly successful in providing efficiently MT
solutions for many language pairs. However, there is a lot of room for
improvement regarding the quality of translations. Prototypical
sentences are translated well but in certain situations the end result
is far from expected. One central reason for the failures is that
current systems take the context into account only in a limited
manner.

In natural language processing, the context of use has a considerable
impact on the understanding process. It can refer to multiple kinds of
meta-data, including information on the document type, domain, genre
and medium used. Automatic machine translation systems typically
restrict the considered context to one sentence or smaller parts of
it.

=== WORKSHOP INFORMATION ===

META-NET Network of Excellence organizes a workshop on Context in
Machine Translation to foster exchange of ideas and results in this
area. The notion of context is meant to be understood broadly,
including other modalities (like vision) in addition to the textual
contexts. Therefore, we expect participants, e.g., from machine
translation, machine learning, vision research and cognitive systems
communities.

The workshop takes place on Tuesday, 14th of June, 2011 at Aalto
University School of Science as a part of ICANN 2011 conference
programme (see http://www.cis.hut.fi/icann11/ for details).

In the workshop, the task and data for Context in Machine Translation Challenge will be
introduced.

=== CALL FOR CONTRIBUTIONS ===

We invite presentations related to the domain of the workshop. This is
an interdisciplinary event and therefore contributions from different
relevant disciplines including language technology, machine learning and cognitive
systems are welcome.

The registration information to ICANN 2011 including conference fees
is available at http://www.cis.hut.fi/icann11/.

If you would like to give a presentation, please send the title and and (extended)
abstract of your presentation in pdf format by 16th of March, 2011 to timo.honkela@tkk.fi
and jaakko.j.vayrynen@tkk.fi. The book of abstracts will be available in the workshop.
The workshop programme will be announced by the end of March, 2011.

If you wish to participate to the workshop without a presentation, please register
normally to the conference and send an e-mail to
jaakko.j.vayrynen(at)tkk.fi by 10th of June, 2011. Please note
15th of April as the deadline for early bird registration.

Research position to work on autonomously motivated exploration and skill acquisition in reinforcement learning

For the EU-funded project CompLACS (Composing Learning for Artificial Cognitive Systems) we are looking for a highly motivated post doctoral researcher in machine learning/reinforcement learning to develop well founded (mathematical) models for autonomous exploration and skill acquisition.

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

This position will be filled in April 2011 for up to four years. Interviews will be conducted in mid March. Depending on your qualification, salary is in the range 35000-45000 EUR per year (after all social and insurance benefits and taxes this is net 24000-30000 EUR). Highly qualified PhD candidates might 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

ECML PKDD 2011 – Call For Discovery Challenge Data/Tasks

Call For Discovery Challenge Data/Tasks

ECML-PKDD 2011: European Conference on Machine Learning and Principles and
Practice of Knowledge Discovery in Databases

September 5-9, 2011, Athens, Greece

http://www.ecmlpkdd2011.org/

The organizing committee of ECML-PKDD 2011 invites the submission of
proposals for the tasks and datasets to be used in ECML-PKDD Discovery
Challenge 2011. The Discovery Challenge provides a venue for the
collaborative exploration and evaluation of novel and interesting
tasks in the areas of Machine Learning and Knowledge Discovery.

The outcome of the Discovery Challenge will be presented in a dedicated
workshop on the first or the last day of the conference, where the
winning and other selected participations will be presented.

* Proposal Guidelines

Submitted proposals should be self-contained and should include at least
the following information:

– Title and abstract of the proposed challenge.
– Contact information of organizer(s).
– General description of the proposed challenge.
– Description of the dataset used in the proposed challenge.
– Description of at least two tasks in which the Discovery Challenge
participants will compete.
– Description of the evaluation procedure and metrics.
– Short biography of organizers, mentioning relevant experience.

The submitted proposals should also consider the following points:

– The dataset should be made publicly available after the end of the
challenge to facilitate future use and repeatability of experiments.
– The dataset should be sufficiently large.
– The tasks should address novel and interesting research problems, which
do not require significant domain-specific knowledge from participants.
– The evaluation procedure should be described clearly.

We encourage organizers to seek awards and prizes for the winning
participants in order to attract participation. The acceptance of a
proposed Discovery Challenge, however, does not depend on the
provision of an award or prize.

* Important Dates

Mar 21, 2011: Discovery Challenge proposal deadline.
Mar 28, 2011: Notification of acceptance.
Apr 11, 2011: Discovery Challenge announcement: Description of tasks, dataset and metrics become available.
Jul 10, 2011: Submission of Discovery Challenge results and reports in
appropriate format.
Jul 21, 2011: Notification of acceptance.
Jul 28, 2011: Submission of Camera Ready Copy for selected submissions.
Sep 5 or 9, 2011: Discovery Challenge workshop at ECML-PKDD 2011.

* Submission of Proposals

Discovery Challenge proposals should be submitted in PDF form by email to
both Discovery Challenge chairs. All submissions will be acknowledged by
email.

* Contact information

If you have any further questions, please do not hesitate to contact us.
We are looking forward to your proposals.

Alexandros Kalousis (Alexandros.Kalousis(at)unige.ch), University of Geneva
Vassilis Plachouras (vplachouras(at)aueb.gr), Athens Univ. of Economics and
Business

MSR PhD studentship available at Edinburgh

A Microsoft Research funded studentship is available at the School of Informatics, University of Edinburgh, to work on machine learning methodology for systems biology. Specifically, the research will involve modelling plants’ circadian clocks; it will be jointly supervised by Dr Guido Sanguinetti (Informatics, Edinburgh) and Prof Chris Bishop (MSR, Cambridge), and will involve collaboration with Prof Andrew Millar’s group at the Centre for Systems Biology at Edinburgh.

For further information and how to apply, please see
http://www.jobs.ac.uk/job/ACG192/microsoft-research-studentship/

RA in Computational Complexity and Behavioural Evolution, Sheffield UK

Research Associate in Computational Complexity and Behavioural Evolution
University of Sheffield, UK
Duration: 18-months with potential for extension
Deadline: 25th March 2011

This post will develop novel approaches to understanding the evolution of animal behaviour, by applying computational complexity and information theoretic approaches to the analysis of mechanisms for implementing animal behaviour. The classic approach to understanding behavioural evolution is in terms of models of optimal behaviour. Optimality theory is invaluable as a benchmark to assess a given behaviour or behavioural model against, but typically requires unrealistic limitations on the behaviour under consideration, and hence results in ‘complex models for simple environments’ [2]. However, real animals inhabit complex environments, and use simple rules of thumb to deal with them [1]. There is clearly a trade-off between the marginal fitness gain from having a more and more complex behavioural model for an environment, and the fitness costs of the additional resources required for implementing that model. To date, the approach to understanding this trade-off has been somewhat heuristic. This project will seek to apply computational complexity theory and information theory in an attempt to gain a more quantitative understanding of the trade- off between behavioural complexity and behavioural optimality.
It is expected that the successful candidate will quickly take a lead in developing a research programme and securing funding to continue it. Researchers who have demonstrated an ability to direct their own research programme, whether during doctoral studies or subsequently, are therefore particularly encouraged to apply. We particularly welcome applications from theoretical computer scientists, theoretical physicists, and mathematicians. A demonstrated interest in biology would be an advantage.
The successful candidate will become part of the newly established Behavioural and Evolutionary Theory Lab at the University of Sheffield, Department of Computer Science, under the directionof Dr James Marshall (http://staffwww.dcs.shef.ac.uk/people/J.Marshall/). It is anticipated that there will be opportunities for interaction with the Modelling Animal Decisions research group directed by Professors Alasdair Houston and John McNamara (Mathematics) at the University of Bristol (http://www.bristol.ac.uk/biology/research/behaviour/mad/).

References
—
[1] Gigerenzer, G., Todd, P.M. et al. (1999) Simple Heuristics that Make Us Smart. Oxford University Press.
[2] McNamara, J.M and Houston, A.I. (2009) Integrating function and mechanism. Trends in Ecology and Evolution 24, 670-675.

For access to the full job advert, visit http://staffwww.dcs.shef.ac.uk/people/J.Marshall/lab/Join_Us.html

2 postdoctoral positions at Cambridge

UNIVERSITY POSTDOCTORAL RESEARCH FELLOWSHIPS IN STATISTICS (2 POSTS)
Department of Pure Mathematics and Mathematical Statistics
Salary: GBP 27,319-?35,646 pa
Limit of Tenure applies*

Applications are invited for two Postdoctoral Research Fellowships in
Statistics, to be held in the Statistical Laboratory.

Informal enquiries can be directed to Professor A.P. Dawid (email:
a.p.dawid(at)statslab.cam.ac.uk).
Further particulars and full details of how to apply can be found at
www.statslab.cam.ac.uk/Vacancies/.

* Limit of tenure: 3 years
Quote Reference: LF07669, Closing Date: 4 March 2011