PhD in Lyon and Rennes (Technicolor lab) in Social Network Analysis

A social network analysis PhD Studentship is available at University of Lyon 2, ERIC lab.
The project is cofounded by the Research center of Technicolor at Rennes in the Media
Computing laboratory, and much of the working time of the PhD student will be spent at Technicolor.

Project title: “Latent Group Dynamics: Evolution of Emergent Roles in Social Networks”.
http://eric.univ-lyon2.fr/~jvelcin/public/misc/phd-technicolor.pdf

Details on this subject can be found in the attached file. We expect that the candidate
has a Master Degree in Mathematics, Computer Science or Cognitive Science and, ideally,
a first research in the field of complex systems.

Applications will be considered until 30 September 2012 but the first successful application
will stop the procedure. Please send your application consisting of curriculum vitae,
the Master thesis (preliminary version, if not finished) and (optional) letters of reference
(to be directly sent to us) directly by email to

Bertrand Jouve (bertrand.jouve@univ-lyon2.fr),
Julien Velcin (julien.velcin@univ-lyon2.fr),
Philippe Schmouker (philippe.schmouker@technicolor.com)
James Lanagan (James.Lanagan@technicolor.com).

PASCAL2 VISIT TO INDUSTRY (LAST CHANCE !): >>>CALL FOR APPLICATIONS <<< Deadline: AUGUST 31, 2012

Deadline: AUGUST 31, 2012

Dear Pascal2 Researchers,

in order to facilitate placement and technology transfer activities, the Pascal2 Internal Visiting Program is inviting applications for student internships at industry organizations. This is specifically devoted to PhD and PostDoc students who are members of Pascal2. We invite both individuals/organizations who have previously sent in an expression of interest, as well as new ones.

The internship should last about 3 months AND FINISH BY THE END OF FEBRUARY 2013, while the host organization can in principle be any enterprise located anywhere in the world. THIS WILL BE THE LAST CHANCE FOR APPLYING TO THIS FUNDING SCHEME WITHIN PASCAL2.

See http://pascallin2.ecs.soton.ac.uk/Programmes/VP/
(“VISIT TO INDUSTRY (LAST CHANCE !)” section) for details.

It is anticipated that the main use of funds under the Pascal2 Visit to Industry stream will be to partially support travel and subsistence for the visit. The program is not intended to cover salaries. Applications should be made by the visitor.

A Pascal2 Visit to Industry proposal should address the following main points:

– Activity description: What is the intern supposed to do ? Why is it interesting/relevant
from a scientific and/or technological viewpoint ?
Why is Machine Learning relevant to this activity ? How and to what extent
the internship is facilitating placement of the intern at the host organization ?
– Information on the host organization: Name, legal form, address, country, number
of employees, short description of enterprise activities
– Name and contact details of the person at the host organization (“tutor”) who
will be in charge of advising the intern, and help with him/her integration in the host
environment
– Content of the training (if any) that will be delivered to the intern
– Contribution granted to the intern by the host organization (e.g., accomodation,
small salary)
– Financial contribution requested to Pascal2 Visit to Industry

Proposals will be evaluated in terms of:
– Scientific and/or technological content
– Training content (if any)
– Host environment integration/placement content
– Practical support provided by the host organization to the intern
– Budget requested to Pascal2 Visit to Industry; normally the maximum
allocation will be 1000 euros per month.

Actual submissions should be done through the Pascal2 Internal Visiting Program at http://pascallin2.ecs.soton.ac.uk/Programmes/VP/
and clicking on the Request tab.

All enquiries should be directed to: claudiogentileuninsubriait

Please send any extra material accompanying the web submission to Claudio Gentile
(claudiogentileuninsubriait) by August 31st, 2012

Post-doctoral Research Associate Adiabatic Quantum Computation

Full details at: https://www.london-nano.com/sites/default/files/PW1249717%20AQC%20JD.pdf

Seeking someone with a background in machine learning, good analytic skills, and willing to learn some small amount of quantum mechanics would be a very good candidate.

LSHC3: ECML/PKDD – PASCAL Discovery Challenge Workshop on Large-Scale Hierarchical Classification

September 28, 2012, Bristol, UK

http://lshtc.iit.demokritos.gr/LSHC3_workshop

*********************************************************

SCOPE

Hierarchies are becoming ever more popular for the organization of documents, particularly on the Web (e.g. Web directories). Along with their widespread use comes the need for automated classification of new documents to the categories in the hierarchy. Research on large-scale classification so far has focused on large numbers of documents and/or large numbers of features, with a limited number of categories. However, this is not the case in hierarchical category systems, such as DMOZ or Wikipedia. Approaching this problem, researchers have either extended existing large-scale classifiers, or have developed new models and methods.

LSHC3 is the third in the series of workshops on large-scale hierarchical classification. The workshop aims at bringing together researchers and practitioners of large-scale category systems and thus welcomes theoretical studies, as well as studies reporting the development of large-scale categorizers or components of such categorizers. In particular, some of the issues that we expect to cover in the workshop are:

* Learning to classify against many categories
* Data sparseness in the presence of large datasets
* Use of the statistical dependence of hierarchically organized classes
* The role of shrinkage methods in large hierarchies
* Ensemble methods for hierarchical classification
* Extending existing large-scale classifiers to hierarchies
* Multi-task and transfer learning within and across large hierarchies
* Unsupervised or semi-supervised extension of hierarchies
* Computational issues in large-scale categorization
* Challenging hierarchical classification tasks and datasets

*********************************************************

IMPORTANT DATES

* Paper submission – July 27
* Acceptance notification – August 10
* Camera-ready paper – August 24

*********************************************************

SUBMISSIONS

We encourage submissions on all aspects of large-scale categorization, from purely theoretical work to practical developments of large-scale categorizers. Submissions must be written in English, following the LNCS guidelines and must not exceed 12 pages including references and figures. The Easychair electronic submission system will be used for the papers. Please, refer to the workshop page for details about the submission format and process.

*********************************************************

ORGANISERS

Ion Androutsopoulos, AUEB, Athens, Greece
Thierry Artieres, LIP6, Paris, France
Patrick Gallinari, LIP6, Paris, France
Eric Gaussier, LIG, Grenoble, France
Aris Kosmopoulos, NCSR “Demokritos” & AUEB, Athens, Greece
George Paliouras, NCSR “Demokritos”, Athens, Greece
Ioannis Partalas, LIG, Grenoble, France

CFP: META-NET Workshop: Machine Translation and Multimodal Contexts

META-NET Workshop: Machine Translation and Multimodal Contexts Special session in ICANN 2012, Lausanne, Switzerland, Sep 11-14, 2012
(http://research.ics.aalto.fi/cog/MTMC2012/)
DL for presentation proposals: 12th of August, 2012

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. One central reason for the failures is that current systems take the context into account only in a limited manner. This is particularly true for multimodal contexts.

This META-NET workshop is organized to foster exchange of ideas and results which combine machine translation and multilinguality challenges with multimodal processing and adaptive systems.

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.

Relevant topics include:
* Specification and standardization of contextual information
* Using textual context in Machine Translation
* Visually informed Machine Translation:
e.g. subtitle translation, personal mobile assistants,
multilingual robotics,semantics of movement

* Speech and sound content in multilingual systems:
e.g. context-aware speech-to-speech Machine Translation,
speaker-based speech adaptation,
recipient-directed speech and translation adaptation,
author and content based style adaptation
* Use of situational and location data
* Machine Translation of colloquial language in rapidly changing
contexts

* Effect of document type, genre, domain of application and medium on
machine translations
* Semantics versus pragmatics in multimodal and multilingual systems
* Tools and corpora for context-aware Machine Translation

* Representing Machine Translation problems in a suitable form for
Neural Network and Machine Learning researchers
* Machine Learning methods and tools for context-aware multilingual
applications
* Studies of human translation performance (with and without context)

* Brain research results on context processing
* Learning correspondences between several languages:
e.g. Meta-learning and multi-task learning for multilingual systems

=== Submission of presentation proposals ===

We invite presentations in the domain of the workshop related to

* completed research results,
* work in progress,
* strategic visions and plans,
* promising ideas, and
* META-NET Challenge: Context in Machine Translation
(http://www.cis.hut.fi/icann11/con-txt-mt11/challenge.php)

Please, send your presentation proposal to timo dot honkela at aalto dot fi and jaakko dot j dot vayrynen at aalto dot fi by 12th of August, 2012. Notification will be sent by 22nd of August.

A presentation proposal consists of a title, presenter, and an abstract.

=== Program and advisory committee ===

Nicola Cancedda, Xerox, France
Jussi Karlgren, SICS, Sweden
Philipp Koehn, University of Edinburgh, UK Markus Koskela, Aalto University, Finland Mikko Kurimo, Aalto University, Finland Krister Lindén, University of Helsinki, Finland Tapani Raiko, Aalto University, Finland Georg Rehm, DFKI, Germany Francois Yvon, LIMSI, France Pierre Zweigenbaum, LIMSI, France

The workshop program and schedule will be published closer to the workshop.

=== Workshop chairs and contact information ===

Timo Honkela, Aalto University (http://users.ics.tkk.fi/tho/) Jaakko Väyrynen, Aalto University (http://users.ics.tkk.fi/jjvayryn/)

UCL PhD Scholarships with Leading Companies

UK PHD CENTRE IN FINANCIAL COMPUTING & BUSINESS ANALYTICS

fully funded for 3 or 4 years

The UK Centre for Financial Computing (www.financialcomputing.org) has a number of PhD
Scholarships jointly funded by UCL and leading companies in the financial and business sectors.
The scholarships are open to UK/EU nationals with exceptional qualifications to work on applied
analytics and computing applications in association with major companies in the financial, retail and
services sectors. The students will spend part of their time at UCL and part at their partner company.
Business Analytics

A recent McKinsey report entitled Big Data: the next frontier for innovation, competition, and
productivity highlighted that Analytics and Big Data is the foremost growth area across all major
research and business sectors, with huge competition for analytics staff. The key skills sought are
computational statistics, machine learning, complexity, so-called big data, and high-performance
computing. PhD students are highly valued and come from all areas of science and engineering (e.g.
Computer Science, Statistics, Mathematics, Physics etc.)

UK Centre in Financial Computing

The UK Centre for Financial Computing (www.financialcomputing.org) is a collaboration of UCL,
London School of Economics, London Business School and the major investment banks. It has over 60 PhD students working on computational finance and business analytics, and another 20 PhD students will start in October. Each student has an Academic Supervisor and an Industry Advisor, and spends an extended period based at their partner company.

PhD Students
We are seeking UK/EU nationals with exceptional
qualifications and experience:

 A strong academic background (based on educational qualifications).

 Strong quantitative skills (ability to learn advanced maths, programming, and statistics).

 Strong research skills (especially in large scale quantitative studies).

 Experience or strong interest in applied research and business.

Applications

To apply email your CV and a Statement of Research interests to:

Prof. Philip Treleaven
Director, UK Centre in Financial Computing
p.treleaven@ucl.ac.uk

Ms. Yonita Carter
Manager, UK Centre in Financial Computing
y.carter@ucl.ac.uk

Postdoc in large scale machine learning

Machine Learning Group, School of Computer Science University of Manchester, UK

A 1-year postdoc position is available in the Machine Learning Group at the University of Manchester, under a team headed by Dr Gavin Brown.
The post is initially for 1 year, renewable for a further year at the discretion of the line manager, based on performance.
The team headed by Dr Gavin Brown focuses on feature selection and extraction from large-scale data, with particular emphasis on statistical (information theoretic) methods. The team has strong ties with the Advanced Processor Tech group in the School, collaborating on multi-core implementations of our algorithms. More information can be found at:

http://mlo.cs.man.ac.uk
http://www.cs.man.ac.uk/~gbrown

JOB DESCRIPTION

You will join a vibrant machine learning team working on information theoretic methods for large-scale feature extraction and selection.
The focus of the job will be adapted to the skills of the applicant. The areas of interest for the team are currently:

-feature selection/extraction filter methods -mutual information and entropy estimation (including non-Shannon) -semi-supervised and positive-unlabelled data sources -streaming data and very large data sources (1TB++) -GPU and multi-core programming methods (e.g. CUDA / Hadoop)

Your primary duty will be to publish high quality research in journal/conference outlets of interest to the group. The secondary duty will be to maintain and develop the software infrastructure for the group, mostly in Matlab/C/C++. Strong guidance will be initially provided, with more freedom allowed with proven ability in the above areas.

The post holder will be encouraged to interact strongly with the Advanced Processor Technologies Group, specifically the many-core systems team headed by Dr Mikel Lujan.

Essential qualifications
•educated to PhD level in Computer Science, with Machine Learning expertise, or for exceptional candidates in the right area, an MSc level qualification (distinction) will be considered.
•proven track record of publications in high quality outlets (e.g. ICML) •strong mathematical literacy in probability theory and linear algebra •strong programming skills, in Matlab/C/C++, ideally in a multi-core environment

********
Informal enquiries should be made in the first case to Dr Gavin Brown, supplying (1) a full academic CV, (2) copies of two best relevant publications.
********

ICNR 2012: Deadline Extension

ICNR 2012
http://www.icnr2012.org/
2012 International Conference on Neurorehabilitation
Converging Clinical and Engineering Research
November 14-16, 2012, Toledo, Spain
Pre-conference workshops: November 13, 2012
Post-conference workshops: November 17, 2012

————————————————————————–
Dear colleague,

It is our great pleasure to invite you to the “2012 Conference on Neurorehabilitation. Converging Clinical and Engineering Research (ICNR2012)” that will take place in Toledo, Spain, from November 14 to 16. The ICNR2012 is endorsed by the International Federation for Medical and Biological Engineering (IFMBE) and IEEE EMBS and will bring together international keynote speakers, researchers and students from the fields of Clinical Rehabilitation, Applied Neurophysiology and Biomedical Engineering.

At this time, we would like to inform you that submission deadline for regular contributions has been extended to July 15. Extended abstract (2 pages) contributions are welcome. All contributions will be peer reviewed. Accepted contributions will appear in Conference Proceedings. Selected papers will be invited to Special Issues in Referred Journals: Journal on Neuroengineering and rehabilitation (JNER) and Journal of accessibility and design for all (JACCES).

We would also like to inform you that there will be an ICNR2012 Paper Competition for undergraduate and graduate students. All contributions will be peer-reviewed. Selected finalists will be asked to prepare a Poster as well as orally present their work in a Student Competition special session. The winner will be awarded with a free inscription to the 2013 Summer School on Neurorehabilitation, where he/she will have the opportunity to get in contact with world-class scientists, and to experience exciting hands-on courses on the most recent technologies (for more information about Summer School please visit the website of 2012 edition: www.ssnr2012.org).
If you are a graduate or undergraduate student willing to participate, you should:

– Submit your Extended Abstract, following to regular procedure described in “Submission Guideline” Section, by July 15.

– During the submission process, please tick the “Student Paper Competition” check box.

NOTE: If you wish to apply but you have already submitted your paper, you can re-enter your EasyChair submission by July 15, and tick the “Student Paper Competition” check box.

WORKSHOPS
WS1- Emerging Therapies in Spinal Cord Injury + VISIT
WS2- Emerging Therapies in Stroke + VISIT
WS3- Rehabilitation robotics for pediatric applications + VISIT
WS4- Pathologic tremor: emerging therapies + VISIT
WS5- Challenges for human centered assistive neuro-robotic devices: experience of the Mundus project
WS6- Creating Intelligent Rehabilitation Technology: An Interdisciplinary Effort
WS7- Extracting the neural strategies from the EMG and implications for myocontrol in neurotechnologies
WS8- Neurorehabilitation Technology: a joint technical, clinical, and basic effort

SPECIAL SESSIONS
SS1- Games and Creativity for NeuroRehabilitation
SS2- Systematic Rehabilitation based on brain rhythm, muscle synergies and tacit learning
SS3- Wearable Robots
SS4- Control strategies in rehabilitation robotics
SS5- Movement analysis techniques in rehabilitation
SS6- How to translate FES from the research to practice
SS7- Improving cognitive and social skills of people with neurological disorders through assistive technologies
SS8- Understanding musculoskeletal deformity and pathological gait: What can musculoskeletal modelling and dynamic gait simulations contribute?
SS9- Sensory Restoration

If you are interested in receiving more detail information, please do not hesitate to contact us.

Looking forward to welcoming you in Toledo!

PhD fellowship at York funded by DSTL

One fully funded PhD fellowship for four years starting
October 2012 is available in the area of

Identifying Human Activities from Video Sequences

under the supervision of Dr. Adrian G. Bors,
Department of Computer Science, University of York, UK.
You will be part of a research group which is well known
internationally in a top rated department in UK.
The PhD fellowship is funded by DSTL and will provide
a salary for up to four years while covering university fees.

The PhD candidate will be expected to develop and implement
new methodologies for processing and analyzing video sequences
showing various human activities. He/she will be required
to develop computational methods for extracting characteristic
features, detect and track human motion. At the higher processing
level, the PhD candidate will develop methods used for
classifying and detecting human activities from image sequences.
This PhD project will require writing research reports and scientific
papers as well as communicating and presenting research results
to DSTL and to the scientific community.

This PhD fellowship is available only for citizens of EU countries.
You will be expected to have an MSc or a good first degree
in one of the fields: Computer Science, Electrical and Electronics
Engineering, Mathematics and Applied Mathematics, or Physics
and have a strong interest in scientific research.
You should have knowledge or a strong willingness to learn quickly
the following:

* Programming skills in Matlab and C
* Good knowledge and understanding of algorithms and
of the mathematics behind them
* Good knowledge of written and spoken English
* Ability to write scientific papers and reports as well as
to present and demonstrate research results

It would be expected that your MSc or final year BSc project was
in an area related to Computer Vision, Pattern Recognition,
Image Processing or Computational Intelligence.

Knowledge and experience with the following would be
highly desirable:

* Processing and analyzing images and image sequences
* Knowledge of applied statistics and mathematics
* Graph representation of data
* Numerical assessment and analysis of experimental results

If you are an EU country citizen and consider yourself as
a suitable candidate for this DSTL funded PhD fellowship
you should send the following by email to adrian.bors@york.ac.uk:

– Your CV
– Short statement of your interest and how would you approach
this research topic
– Short description of your final year or MSc project
– Transcripts with marks achieved during your previous study
– List of scientific papers published or submitted, if any
– Other relevant major achievements
– Names of two academic persons who can provide references
for you if requested

PhD funding available: 4 years

Start date: October 2012

Location: Dept. of Computer Science
University of York
York, UK

Contact: Dr. Adrian G. Bors
E-mail: adrian.bors@york.ac.uk

http:\www-users.cs.york.ac.uk/~adrian/

All candidates will be considered for a preliminary selection
and those with the strongest profiles will be contacted.

Fully-funded 4-year PhD studentship in in “Statistical Signal Processing and Machine Learning for Network Traffic Anomaly Detection”

* £17,000 per annum tax-free stipend + full UK/EU fees + annual conference travel budget.

* Applicants must be UK/EU nationals.

* The candidate must start October 2012.

* Application Deadline: 31st July 2012.

This project will develop advanced multivariate statistical and machine learning methodology for the analysis of network traffic measurement data. The aim is to deliver robust detection of hostile cyber activity. Several open problems will be addressed, including the choice of background model, features, and classifiers; and possible incorporation of multiresolution inferential methodology, which may include extensions to wavelet-Bayesian Markov chain Monte Carlo change point approaches.

The ideal candidate will have a strong interest in exciting recent developments in the convergent disciplines of computational statistics, machine learning, and signal processing.

The research will be undertaken within the UCL Security Science Doctoral Training Centre (UCL SECReT) see and the UCL Dept of Statistical Science . The research is funded by the UK Ministry of Defence and will involve some collaboration with the Defence Science and Technology Laboratory.

For informal enquiries, please contact the principal supervisor, Dr. James Nelson, UCL Department of Statistical Science: .

For information on how to apply, please see:

www.ucl.ac.uk/secret/secret_news/statistical-signal