PhD studentship and bioinformatician post on the genetics of ageing

PhD Studentship: The Integrative Genomics of Ageing Group at the University of Liverpool is accepting applications for a PhD studentship available for start in the autumn of 2013. We are looking for an enthusiastic and ambitious student to develop and apply sophisticated data-mining methods and computational models at the interface of biology, mathematics and computer science. The sequencing of genomes has opened unparalleled opportunities to compare multiple genomes and identify coding or DNA regulatory sequences that modulate ageing in humans or determine species differences in ageing and longevity. There is also an urgent need to understand how genes associated with ageing collectively regulate the ageing process. We are analysing gene expression data and developing gene networks to deepen our knowledge of how genes interact with each other and with the environment to gain new insights into the genetics of ageing and identify new candidate genes for experimental validation. The exact direction of this project, however, will be adapted to fit the research interests of the student. Though this project is primarily computational, our group also has wet lab facilities and thus it is possible to experimentally validate any computational predictions emerging from this project.

This studentship is in competition for funding with others at our institution. The funding is only available to UK citizens and residents. Non-UK students interested in our group’s work, however, are encouraged to contact us as it may be possible to apply for personal fellowships. Self-funded students are also invited to apply.

Bioinformatician: A bioinformatician position is also available in our group to employ computational biology approaches to study ageing and longevity. As above, areas of interest include (but are not limited to) systems biology, functional genomics, network analysis, and genome evolution. Applicants should have a degree in computer sciences or biology with experience in programming languages, ideally in context of bioinformatics and genomics. Relevant publications would be a plus. The post is available for one year in the first instance but can be renewed depending on performance and funding.

More details about our research are available at:
http://pcwww.liv.ac.uk/~aging/

Potentially interested students are welcome to contact us for an informal discussion (aging@liv.ac.uk or 0151 7954517).

Professor (W2) “Machine Learning” in Oldenburg, DE

The University of Oldenburg, Germany, is seeking to fill as soon as
possible the position of an associate professor (W2) in “Machine
Learning”. The successful candidate should contribute in a meaningful
way to the existing research focus areas speech processing, auditory
scene analysis, pattern recognition and communication acoustics. She/he
should exhibit links to the topics of the cluster of excellence
Hearing4All, e.g. in statistical signal processing or in numerical
modeling and realtime experimental control. More information can be
found on http://www.uni-oldenburg.de/stellen/?stelle=61380. The
application deadline is 31 January 2013.

Extended deadline 4 February: Call for Contributions to Final PASCAL2 review Meeting – Palma de Mallorca – 11 April 2013

Dear Pascal2 Researchers,

A reminder about the below call. You can submit your papers at https://www.easychair.org/account/signin.cgi?conf=mlcogs2013

All good wishes,

Victoria

From: Shawe-Taylor, John
Sent: 06 December 2012 15:35
To: researchers@pascal-network.org
Subject: Call for Contributions to Final review Meeting

Dear Pascal Researchers,

We have arranged to hold our final review meeting in Palma de Mallorca collocated with a EUCOGIII Network meeting. We have the afternoon of April 11 set aside to highlight some of the research that has been carried out within the network and propose to organise this as a series of spotlight presentations and poster sessions in order to enable maximum interaction with members of the review panel and EUCOGIII Network.

We therefore invite contributions in the form of a summary (not exceeding 4 pages in NIPS 2012 style) of the work to be presented highlighting its potential impact and where appropriate relevance to Cognitive Systems. For those papers selected all costs of attending the meeting will be covered either by PASCAL central funds or EUCOGIII.

What’s in it for you:
• Chance to be highlighted as a key researcher within PASCAL with your work remaining visible through a publication in the journal of machine learning video abstracts (see http://videolectures.net/machine_learning_video_abstracts_vol1/)
• chance to promote collaboration with cognitive scientists
• free trip to Mallorca.

I am currently recruiting members of the programme committee for this event, but below is a list of those who have already agreed to be involved. The deadline for submission will be 4th Feb – details of how to submit will follow in the New Year.

Many thanks
John

PASCAL/EUCOGIII Joint Session on Learning
Programme Committee Members
Sami Kaski
Dunja Mladenic
Moritz Grosse-Wentrup
Peter Auer
Florence d’Alche-Buc
Alfons Juan
Vincent Muller
David Barber

Reminder: ECML/PKDD 2013 Call for Workshop Proposals

The ECML/PKDD-2013 Organizing Committee invites proposals for workshops to be held on the first and last days of the conference, which will take place in Prague from September 23rd to 27th, 2013. We invite proposals for full-day workshops in relevant and current topics in Machine Learning and Data Mining. The scope of the proposal should be consistent with the conference themes as described in the ECML/PKDD 2013 Call for Papers (http://www.ecmlpkdd2013.org/first-call-for-papers/).
Workshops provide an opportunity to discuss current topics in a small and interactive atmosphere. They can concentrate in-depth on research topics, or be devoted to application issues, or to questions concerning the economic and social aspects of machine learning and data mining. Interdisciplinary workshops that bring together researchers and practitioners from different communities are especially welcome. We encourage workshops that bridge the gap between theoretical advances and important applications of machine learning and data mining.
Workshops are expected to cover a full day, with a program of typically 7 hours including a 30-minute coffee break and a 90-minute lunch break. We would like to encourage proposers to aim for a program that is both varied and interesting. Especially where the format of the workshop is concerned, we would like you to think about ways of going beyond the usual list of presentations of accepted papers, for example by means of panels, discussions, demo sessions and invited talks. For some workshops, it may be preferable to first present an introduction to the state of the art in the field given by experienced invited presenters, and afterwards discuss more technical or novel work in a standard workshop setting. Another way of extending the usual format is to include a specific challenge problem that can be addressed by the workshop participants, with a dedicated challenge session in the workshop program. Note that the challenge should be only one of the components of the workshop, targeting a problem which is specific to the workshop topic(s). Proposals focusing mainly on challenge problems should be submitted to the Discovery Track.
In general, workshop proposals that show creativity as to the format will be judged favourably in the proposal selection. Furthermore, having ideas for follow-up to your workshop, in terms of for example a book or journal special issue, will help to attract more submissions, and make your workshop (proposal) a success.
We encourage workshops on novel and original topics, but also welcome successors to workshops that have been organized at ECML/PKDD or a related conference in the past. For successor workshops, proposers should motivate how another instance of the workshop series will address novel developments in the respective research field, and should be able to show that the previous edition(s) were successful in terms of paper submissions and attendance.
Guidelines for proposals
Workshop proposals should contain the necessary information for the workshop chairs and reviewers to judge the importance, quality and community interest in the proposed topic. Each workshop should have one or more designated organizers and a workshop program. When proposing a workshop, please provide (at least) the following information:
• A brief description of the specific issues that the workshop will address, the reasons why the workshop is of interest in these times, the main research areas involved.
• Contact information of the workshop chairs, their competence in the proposed topic(s) and previous experience in chairing scientific events.
• A tentative list of Program Committee members.
• A draft of the Call for Papers, including information on accepted formats (e.g. regular papers, extended abstracts, oral only presentations of relevant recently published or submitted contributions, etc.) and expected format of the workshop (e.g., invited talks, presentations, poster sessions, panel discussions, or other ideas for ensuring an interactive atmosphere).
• Any special requirements regarding logistics (e.g. poster stands, more than one projector), if applicable.
Please submit your workshop proposals by e-mail to the ECML/PKDD workshop chairs (see contact information below). Proposals will be reviewed in close collaboration with the conference chairs and the program committee.
Important dates
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
For paper submission, reviewing and final revisions, please consider the following deadlines:
• Workshop paper submission deadline: Friday, June 28, 2013
• Workshop paper acceptance notification: Friday July 19, 2013
• Workshop paper camera-ready deadline: Friday August 2, 2013

These deadlines are somewhat flexible, but consider as constraints that the paper submission deadline should be after conference author notification and acceptance notification should be before the conference early registration deadline.
Contact
In case you have any question, please do not hesitate to contact us. We are looking forward to your proposals. The ECML/PKDD 2013 workshop chairs:
• Andrea Passerini (University of Trento)
• Niels Landwehr (University of Potsdam)

Please send emails to workshops@ecmlpkdd2013.org

ImageCLEF 2013 Scalable Concept Image Annotation – Call for participation

ImageCLEF 2013 Scalable Concept Image Annotation – Call for participation http://imageclef.org/2013/photo/annotation

We cordially invite you to participate in this year’s Scalable Concept Image Annotation challenge, one of the subtasks of ImageCLEF (http://imageclef.org/2013). ImageCLEF is one of the labs of CLEF 2013 (http://clef2013.org), which this year will be held in Valencia, Spain.

The challenge addresses the problem of automatically annotating a (possibly very large) database of images, an important process in order to reliably index and later retrieve images from this database. Image concept detection generally has relied on training data that has been manually, and thus reliably annotated – an expensive and laborious endeavor that cannot easily scale, especially when the number of concepts grows. To address this issue, this task proposes to develop annotation systems by relying only on automatically obtained web data. The text surrounding the images in webpages frequently has relation to the content of the images, making it a useful, albeit very noisy, source of data.
The participants need to develop a system using only a provided training set of images and associated text, and optionally other resources that do not require labeling, e.g. more unlabeled images, WordNet, dictionaries, etc. Participating can be as simple as naively using the text data to define the presence or absence of concepts and then use an already existing supervised-based method, so we encourage you all to take part in the task.

The participants will have a chance to submit a paper describing their system, which will be published in the CLEF Labs Working Notes.
Furthermore, the groups of the best performing systems will be invited to give an oral presentation at CLEF 2013.

For more details on the task please visit http://imageclef.org/2013/photo/annotation

Schedule:
15/12/2012: Registration opens
07/01/2013: Training and Development sets available
07/01/2013: Development set baseline toolkit available
15/03/2013: Test set available
15/04/2013 — 22/04/2013: Submission system for runs is open
25/05/2013: Submissions results released
15/06/2013: Deadline for submission of working notes papers
23/09/2013 — 26/09/2013: CLEF 2013 Conference, Valencia, Spain

Organizers:
* Mauricio Villegas, PRHLT, Universidad Politécnica de Valencia, Spain, mvillegas@iti.upv.es
* Roberto Paredes, PRHLT, Universidad Politécnica de Valencia, Spain, rparedes@dsic.upv.es
* Bart Thomee, Yahoo! Research, Spain, bthomee@yahoo-inc.com

POSTDOC IN MACHINE LEARNING FOR SOCIAL SIGNAL PROCESSING

In highly dynamic environments such as airports, using robots to navigate and
interact with individuals and groups of people is very challenging. The EU
STREP project SPENCER aims at developing these capabilities.

We are offering a 2 year full time postdoctoral position, which is a
collaboration between the University of Twente and Delft University.
The position will be embedded in the Pattern Recognition and BioInformatics
Group (http://prb.tudelft.nl/) at the Technical University of Delft, working
closely with Dr. Hayley Hung and employed by the Human Media Interaction Group
(http://hmi.ewi.utwente.nl/) at the University of Twente.

The postdoc will be required to carry out novel research work on devising
methods to automatically analyse social group behavior to facilitate better
human-robot interaction. This involve cross-disciplinary research methods, using
findings in social psychological research to inspire the design of computational
models that automatically interpret socially relevant characteristics of
individuals and groups. The successful candidate will have the opportunity to
work with a trans-European research team (University of Aachen, University of
Freiburg, etc). The successful applicant will also gain valuable experience in
carrying out research, while also having contact with industrial partners
(BlueBotics, KLM) to transform the research findings into a working
demonstrator. There will also be opportunities to participate in various
national and international conferences and workshops etc.

==============================================================
*Your Profile:*
==============================================================
All applicants should have or expect to obtain a PhD within four months of
commencing the position. Interested applicants should have a strong background
in some or all of the following subjects, or a related discipline:
social signal processing, machine learning, computer vision, signal processing,
affective computing, social computing, pattern recognition. Experience working
with models for sensor and/or data fusion is a bonus.

The successful applicant will have:
– a proven track record in carrying out excellent research;
– a strong publication record in international conferences and journals;
– 3+ years programming experience;
– curiosity and good analytical skills;
– the ability to work in a multi-disciplinary team;
– motivation to meet deadlines;
– an affinity with the relevant social science research;
– excellent oral and written communication skills;
– an interest in communicating their research results to a wider audience;
– proficiency in English;
==================================================================
*Application procedure:*
==================================================================
Interested applicants should send an up to date curriculum vitae (with a
complete list of publications), letter of application, and the names and the
contact information (telephone number and email
address) of three references.

The letter of application should summarise (i) why the project is of interest to
the applicant, (ii) evidence of suitability for the job, (iii) the applicant’s
research contributions in the previous 3-5 years, and (iv) what the applicant
hopes to gain from the position.

If you have any questions about the position, please contact Dr. Hung at
hayleyhung@gmail.com, strictly for information about the position.

All applications material should be uploaded via the University of Twente vacancies page:
http://www.utwente.nl/vacatures/
(click on the link ‘Postdoc Position in Social Computing’ and then ‘Apply Now’)

Please submit applications on or before February 8, 2013. Late applications may
be also be considered but early applications will be given priority.

Further information about our offer and the institutions can be found at:
http://www.utwente.nl/vacatures/
(click on the link ‘Postdoc Position in Social Computing’)

2 Postdoc positions in Natural Language Processing – Information Retrieval at KU Leuven

The KU Leuven offers an F+ fellowship to an outstanding postdoctoral researcher who is specialized in natural language processing and machine learning. The work will be conducted in the framework of the EU FP7 MUSE research project (http://www.muse-project.eu/) granted under the Future and Emerging Technologies ICT call. The candidate is holder of a PhD degree, and should have published several papers in any of the following journals or conferences:
• Computational Linguistics, Computer Speech and Language, Artificial Intelligence, Journal of Machine Learning Research, Machine Learning, IEEE Intelligent Systems
• Proceedings of ACL, EACL, NAACL-HLT, COLING, IJCAI, ICML, ECAI.

The position will be for one year starting in the late Spring or Summer 2013 and can be prolonged. He or she has a large interest in “machine reading” and semantic processing of text. The candidate has completed the PhD with success as evidenced by multiple publications in the venues cited above. He or she must have obtained a PhD from a university other than KU Leuven and must preferably have an international profile. He or she has a master degree (cum laude) in computer science, electrical engineering, mathematics, physics or a related discipline. The candidate does not have a postdoctoral status for more than six years. In order to be taken into consideration, the candidate must be available on a full-time basis. Furthermore, the candidate has excellent English language skills (written and spoken), good communication skills especially for guiding master and PhD students, good programming skills (e.g., Java, C++, MATLAB, Python) and has the capability to work independently and in a team.

Please send your application to Marie-Francine Moens the latest by March 15, 2013. Please add a CV, grade transcripts, and publication list. Reference letters may be useful as well.

——————————————————————————————————–

The Language Intelligence and Information Retrieval team, which is part of the Human Computer Interaction group at the Department of Computer Science at KU Leuven (http://www.cs.kuleuven.be/groups/liir/), has an open position for a postdoctoral researcher specialized in information retrieval. The work will be conducted in the framework of the EU FP7 TOSCA-MP project (http://tosca-mp.eu/) and the SBO-IWT PARIS project (http://www.parisproject.be/). The position will be for two years starting in the Spring or Summer 2013. The candidate is holder of a PhD degree, and should have published several papers in any of the following journals or conferences:
• Information Retrieval, Information Processing and Management, ACM Transactions on Information Systems
• Proceedings of SIGIR, ECIR, CIKM, WWW.

The candidate has a large interest in multimedia and advertisement retrieval. He or she has a good knowledge of ranking and aggregation models, structured output learners, dimensionality reduction and latent class models. The candidate has completed the PhD with success as evidenced by multiple publications in the venues cited above. He or she has a master degree (cum laude) in computer science, electrical engineering, mathematics, physics or a related discipline. Furthermore, the candidate has excellent English language skills (written and spoken), good communication skills especially for guiding master and PhD students, good programming skills (e.g., Java, C++, MATLAB, Python) and has the capability to work independently and in a team.

Please send your application to Marie-Francine Moens the latest by March 15, 2013. 
Please add a CV, grade transcripts, and publication list. Reference letters may be useful as well.

PhD position

PhD position in Signal Processing and Machine Learning for Stress Level Assesment Signal Processing Group Department of Signal Theory and Communications Universidad Carlos III de Madrid

The Signal Processing Group invites applications for a fullly funded PhD scholarship in Signal Processing and Machine Learning. The PhD work is part of a project devoted to the development of indicators of stress level from electrodermal activity sensors, inertial and vision, and is funded by CASSIDIAN. The PhD work will be supervised by Antonio Artés and will be conducted in collaboration with a team of psychiatrists, neurologists and CASSIDIAN staff.
The appoinment is for a period of 4 years, and the scholarship will start as soon as possible.
Applicant must have:
• An MSc in Electrical Engineering, Computer Science, Mathematics, Physics or related disciplines.
• A BSc/An MSc Thesis within Signal Processing and/or Machine Learning.

Applications must be sent to Antonio Artes (antonio@ieee.org) and must include:
• Curriculum vitae
• Copy of the BSc or MSc Thesis
• Copies of publications (if any)
• Complete list of grad for all examns during bachelor and master educations • Name and email address of two references

Amazon Europe Machine Learning Team Coming To Berlin!

Amazon is building a European Machine Learning (ML) team in Berlin! Machine Learning Scientists at Amazon are technical leaders who develop planet-scale platforms for machine learning on the cloud, assist the benchmarking and future development of existing machine learning applications across Amazon, and help develop novel and infinitely-scalable applications that optimize Amazon’s systems using cutting edge quantitative techniques. The ML team innovates algorithms that model patterns within data to drive automated decisions at scale in all corners of the company, including our eCommerce site and subsidiaries, Amazon Web Services, Seller & Buyer Services and Digital Media including Kindle. Amazon was one of the first companies to build eCommerce customer recommendations, fraud detection, and product search using machine learning innovations. Being part of the Machine Learning team at Amazon is one of the most exciting machine learning job opportunities in the world today. If you have deep technical knowhow in Machine Learning, know how to deliver, are deeply technical, highly innovative and long for the opportunity to build solutions to challenging problems that directly affect millions of people: there may be no better place than Amazon for you to impact the world!

If you are interested send your CV to strategic-recruiting@amazon.com.

We are hosting a week-long interview event on March 12 – 16, 2013 in Berlin, Germany. The basic qualifications are:
• A PhD in Computer Science, Applied Math, Statistics, Operations Research or a highly quantitative field
• 5+ years of hands-on experience developing and implementing Machine Learning algorithms and models
• Programming and prototyping skills.
• Solid communication and data presentation skills.
• Problem solving ability.
• A strong track record of innovating in Machine Learning algorithms and applications.
• Strong demonstrated skills implementing and deploying large-scale Machine Learning applications and tools.
• Strong skills programming in Java/C++ and R/Python

2 Postdoc positions in “Machine Learning / Information Retrieval / Natural Language Processing” at XRCE

The Machine Learning for Document Access and Translation group of the Xerox Research Centre Europe (Grenoble / France) conducts research in Statistical Machine Translation and Information Retrieval, Categorization and Clustering using advanced machine learning methods.
We are opening two positions for researchers (temporary positions equivalent to PostDoc) with a background in Machine Learning, Information Retrieval or statistical Natural Language Processing to support our activities.
Required experience and qualifications:
• PhD in computer science, mathematics, statistics, or computational linguistics with focus on Machine Learning, Information Retrieval, or statistical NLP.
• Good publication record and evidence of implementing systems.
• A good command of English, as well as open-mindedness and the will to collaborate within a team.
Additional desirable skills:
• Multi-modal data mining
• Multilingual document access
• Sentiment analysis/opinion mining
• Information visualisation.
XRCE is a highly innovative place and we strongly encourage publication and interaction with the scientific community.
Starting date
ASAP
Application instructions
Inquiries can be sent to Jean-Michel.Renders at xrce.xerox.com and Nicola.Cancedda at xrce.xerox.com.
More details on:
http://www.xrce.xerox.com/About-XRCE/Career-opportunities/Researcher-Machine-Learning-Information-Retrieval-Natural-Language-Processing-2-positions