Postdoctoral position at the University of Paris-Sud/CNRS

The Machine Learning (AppStat) group of the Linear Accelerator Laboratory (LAL) is seeking a postdoctoral researcher for working on machine learning motivated by experimental physics. The position is financed by the ANR Siminole project (http://siminole.lal.in2p3.fr). Some of the ongoing themes are large scale MCMC in hierarchical parametric models, budgeted learning for real-time triggers, and unsupervised (deep) feature learning for next-generation high-resolution pixel calorimeters. All themes include the development of state-of-the-art ML solutions that can make a real difference in both the design and in the data analysis phases of ongoing and future large-scale physics experiments (e.g., Auger, LHCb@CERN, the future ILC or JEM EUSO). The ideal candidate should have a recently completed Ph.D. in the areas of machine learning or computational statistics, and an open spirit to work with researchers of different disciplines.

AppStat (http://appstat.lal.in2p3.fr) is an interdisciplinary research group with the mission of creating a scientific link between experimental physics and machine learning. AppStat is part of the Linear Accelerator Laboratory (LAL) and it also has strong ties to the Machine Learning and Optimization team (http://tao.lri.fr) of the Computer Science Laboratory (LRI). Both laboratories are part of the University of Paris-Sud campus, located in the outskirts of Paris. The position is available for a period of two years starting in February, 2013. The monthly salary is in the 2500-3000 euro range depending on experience. Interested candidates should send a cover letter, a curriculum vitae, and the names and addresses of three referees before December 20, 2012 to Dr. Balázs Kégl (balazs.kegl@gmail.com), and should be ready for an interview in the beginning of January.

PS: I will be at NIPS, don’t hesitate to contact me if you would like to discuss the position.

ESANN 2013: deadline extension

ESANN 2013

21st European Symposium on Artificial Neural Networks,
Computational Intelligence and Machine Learning
Bruges (Belgium) – April 24-25-26, 2013
http://www.esann.org/

Submission deadline extension
======================================================

Due to numerous requests, the deadline to submit papers to the ESANN 2013 conference has been extended to December 7, 2012. Please note that no further extension will be given.

Looking forward to seeing you at ESANN 2013,
The organizing committee.

========================================================
ESANN – European Symposium on Artificial Neural Networks,
Computational Intelligence and Machine Learning
http://www.esann.org/

* For submissions of papers, reviews, registrations:
Michel Verleysen
Univ. Cath. de Louvain – Machine Learning Group
3, pl. du Levant – B-1348 Louvain-la-Neuve – Belgium
tel: +32 10 47 25 51 – fax: + 32 10 47 25 98
mailto:esann@uclouvain.be

* Conference secretariat
d-side conference services
24 av. L. Mommaerts – B-1140 Evere – Belgium
tel: + 32 2 730 06 11 – fax: + 32 2 730 06 00
mailto:esann@uclouvain.be
========================================================

Positions at LSE

The LSE (London School of Economics) has advertised twenty new positions across all its departments (which include mathematics and statistics) and at all levels, from lecturer (=assistant professor) to professor (=full professor). See http://www.lseglobaldebate.com
The deadline is 7 December.

LSE, as a Social Sciences university, does not have a computer science department or departments in traditional sciences, but has active research groups in the areas of discrete mathematics and algorithms, game theory, financial mathematics, and many areas of statistics.

It’s an open recruitment exercise, in the sense that departments have not each been given fixed numbers of positions, but essentially will be in competition with each other for the positions. So it is a fairly unusual hiring exercise. When applying, candidates are asked to indicate which department they would want to belong to (and interdisciplinary will be likely to be viewed positively). If you might be interested in applying, with a view to joining the Mathematics department (and/or the Statistics department, with whom we work closely), and would like to discuss, please contact me (m.anthony@lse.ac.uk) and/or the head of the Mathematics department, Jan van den Heuvel (j.van-den-heuvel@lse.ac.uk).

Phd position in active perception and control at the University of Amsterdam

The Informatics Institute at the University of Amsterdam invites applications for a fully funded position for a PhD student in the area of active perception and control. The position is within the Intelligent Systems Lab Amsterdam and will be supervised by dr. Gwenn Englebienne and dr. Shimon Whiteson.

Application closing date: 15 December 2012, or until position is filled
Starting date: 1 February 2013
Duration: 4 years

The research will focus on the development of active perception and control algorithms for teams of robots. This will require advancing the state of the art in computer vision, multimodal perception, and decision-theoretic planning and learning. The research will be conducted as part of a European project called “Multi-Robot Cognitive Systems Operating in Hospitals (MOnarCH)” in which the University of Amsterdam collaborates with several other European universities and companies. The project aims to develop a network of heterogeneous robots and sensors for deployment in the pediatric area of an oncological hospital. It will handle uncertainties introduced by people and robots, generate natural interactions, and engage in edutainment activities.

Applicants must have a master’s degree in computer science or a closely related area. In addition, a successful candidate should have:

* strong math and programming skills.

* strong background in artificial intelligence: particularly useful is knowledge of machine learning, reinforcement learning, robotics, and computer vision. Experience with human-computer interaction and multimodal interfaces are a plus.

* strong oral and written communication skills.

The successful candidate will be based in the Intelligent Systems Lab Amsterdam (ISLA) within the Informatics Institute at the University of Amsterdam. The institute was recently ranked among the top 50 computer science departments in the world by the 2011 QS World University IT Rankings. ISLA consists of 20 members of faculty, 20 postdoctoral researchers, and more than 50 PhD students. Members of the lab are actively pursuing a variety of research initiatives, including machine learning, decision-theoretic planning and learning, multiagent systems, human-computer-interaction, natural language processing, information retrieval, and computer vision.

Some of the things we have to offer:

* competitive pay and excellent benefits
* extremely friendly working environment
* high-level of interaction
* location near the city center (10 minutes by bicycle) of one Europe’s most beautiful and lively cities
* international environment (10+ nationalities in the group)
* access to high-end computing facilities (cluster with 4,000+ cores)
* brand-new building

Since Amsterdam is a very international city where almost everybody speaks and understands English, candidates need not be afraid of the language barrier.

For further information, including instructions on submitting an application, see the official job ad at bit.ly/STd3O2.

Informal inquiries can be made by email to Gwenn Englebienne (g.englebienne@uva.nl) and Shimon Whiteson (s.a.whiteson@uva.nl).

PhD studentship in “Machine intelligence” at QMUL

Queen Mary University of London, School of Electronic Engineering and Computer Science
PhD studentship in “Machine intelligence”

Applications are invited for a PhD Studentship starting in September 2013 within the Risk Information Management group.

The focus of this doctoral research project is on lifelong machine learning. Traditional machine learning methods learn each new problem from scratch, requiring extensive training each time. In contrast, humans rapidly learn to solve new and complex problems with limited practice by building on a lifetime of experience with related tasks and domains. The goal of this project is to develop models for lifelong machine learning, enabling experience from each encountered task and domain to be accumulated and exploited in the next. A variety of applications can be considered as lifelong machine learning has potential to impact diverse areas including computer vision, security, forensics, medical diagnosis, big data, ecommerce and others. A strong foundation in mathematics (linear algebra, calculus and statistics) and programming are essential.

The studentship will be based in the School of Electronic Engineering and Computer Science (EECS) www.eecs.qmul.ac.uk at Queen Mary University of London, in the Risk and Information Management Group which has a world-leading reputation in the area of risk assessment. The RIM group undertakes interdisciplinary research in decision analysis and risk, databases/information retrieval, personalisation, learning, uncertainty, and Bayesian methods. Much of the research involves combining data and human expertise to create intelligent solutions for high stakes decisions. We work with practitioners to produce intelligent ‘unified models’ (typically causal Bayesian networks) that use both data and expertise as inputs, to support expert decision making in multiple application domains. The group is currently working on improved decision making in medical, legal, systems engineering, security and safety applications.
This position, funded by a Queen Mary Prinicipal’s studentship, is for 3 years and will cover student fees and a tax-free stipend starting at £15,590 per annum. Applicants of all nationalities are invited to apply. Candidates should have a first class honours degree or equivalent, or a strong Masters Degree, in computer science, mathematics, physics or electronic engineering. For queries please contact Dr. Timothy Hospedales tmh@eecs.qmul.ac.uk.

To apply please follow the on-line process (see www.qmul.ac.uk/postgraduate/apply ) by selecting “Computer Science” in the “A-Z list of research opportunities” and following the instructions on the right hand side of the web page.

Please note that instead of the ‘Research Proposal’ we request a ‘Statement of Research Interests’. Your Statement of Research Interest should answer two questions: (i) Why are you interested in the proposed area? (ii) What is your experience in the proposed area? Your statement should be brief: no more than 500 words or one side of A4 paper. Mark clearly the statement with your name and the student ship title “Machine Intelligence”. In addition we would also like you to send a sample of your written work. This might be a chapter of your final year dissertation, or a published conference or journal paper. More details can be found at: www.eecs.qmul.ac.uk/phd/apply.php

The closing date for the applications is 31 January 2013.
Interviews are expected to take place during February 2013.

Postdoc: probabilistic ML and household energy usage

We are seeking a postdoctoral researcher at the University of Edinburgh to work on a project involving probabilistic inference and machine learning methods to help households understand and reduce their energy usage. This position is part of a new £2M project that will involve work on a data set of household energy usage of unprecedented size and scope.

The project would be suitable for candidates with a strong background in probabilistic machine learning who would like to gain more experience in applications of machine learning to sustainability.

The researcher will be a part of the School of Informatics at the University of Edinburgh. This is an opportunity to work in a world-leading machine learning group, including seven faculty in the area. More broadly, a recent international review described the School as an “elite” department of computer science in Europe, and in national research assessment exercises, the School of Informatics has consistently ranked at the top in the UK for research quality.

The postdoctoral researcher will be jointly supervised by Charles Sutton and Nigel Goddard , either of whom may be contacted for informal enquiries.

For more information about the project and information about how to apply, please see
http://www.energyoracle.org/machine-learning-postdoc.html

Please note the closing date of FRIDAY 14 DECEMBER 2012, at 5pm UK time.

Research scientist position: statistical genomics and computational biology

We are seeking to employ an enthusiastic Research Scientist/Bioinformatician to join the Statistical Genomics and Systems Genetics Group at the European Bioinformatics Institute (EMBL-EBI) located on the Wellcome Trust Genome Campus near Cambridge in the UK.
The goal of the research group is to devise computational and statistical approaches to understand the interplay of genotype, cellular factors and external influences and their implications for phenotype. Our research is hypothesis-driven and tailored towards answering pertinent biological questions from high-throughput omics datasets.

We combine statistical machine learning with mechanistic modelling concepts to integrate genotype information, molecular profiling data and other phenotypic information. Current research directions include the development of statistical methodology for genome-wide association studies, methods to dissect the genetic architecture of molecular traits and causal modelling to predict functional targets for molecular intervention. Our methodological research aims are embedded in close collaborations with experimental partners.

The successful applicant will hold a doctoral degree or equivalent qualification in computer science, mathematics, physics, and/or engineering. We especially seek candidates with prior experience in statistical aspects of systems biology projects, including gene expression data analysis, GWAS and analysis of NGS data. A foundation and background in statistics, machine learning, optimization and dynamical systems is very beneficial. A background in biology, or previous experience tackling biological questions is desirable but not necessary.
For informal enquiries contact Oliver Stegle . Applications should be made online (deadline 23. November). For further details and application instructions, see http://ig14.i-grasp.com//fe/tpl_embl01.asp?newms=jj&id=49988&aid=15470.

Multiple Postdoctoral Programs at the Israeli center research excellence in Algorithms

The Israeli center research excellence in Algorithms is seeking excellent postdoctoral candidates for our postdoctoral programs:

* I-CORE in Algorithms and the Simons Institute for the Theory of Computing in Berkeley –
a joint postdoctoral program

http://www.icore-algo.org.il/?q=content/i-core-algorithms-and-simons-institute-theory-computing-berkeley-joint-postdoctoral-program

* Leonardo Fibonacci fellowships –
a joint postdoctoral program of I-CORE Algo, CNR and ENEA

http://www.icore-algo.org.il/?q=content/leonardo-fibonacci-fellowships-joint-postdoctoral-program-i-core-algo-cnr-and-enea

* I-CORE in Algorithms postdoctoral program:

http://www.icore-algo.org.il/?q=content/i-core-algorithms-postdoctoral-program

Topics of interest include (but are not limited to): all variety of algorithms
(optimization, online, streaming, approximation, randomized, geometric and more), cryptography,
security and privacy, algorithmic game theory, quantum computing, networking and distributed computing,
databases, machine learning and computer vision.

***

The Israeli Center of Research Excellence in Algorithms is part of the I-CORE program,
initiated by the Government of Israel and adopted by Israel’s Council of Higher Education,
in order to reinforce Israel’s intellectual capacities and promote synergy among Israel’s leading research centers.

The institutes participating in the center are:
* The Blavatnik School of Computer Science, Tel Aviv University
* The Rachel and Selim Benin School of Computer Science and Engineering, The Hebrew University of Jerusalem,
* Faculty of Mathematics and Computer Science, Weizmann Institute of Science.

* for more information about the I-CORE ALGO please see http://www.icore-algo.org.il/
and regarding the post-doc programs see http://www.icore-algo.org.il/?q=content/post-doc-programs

IbPRIA 2013 – 6th Iberian Conference on Pattern Recognition and Image Analysis

Madeira, Portugal
June 5-7, 2013
http://www.ibpria.org/2013

IMPORTANT DATES
Submission of papers: November 30, 2012
Notification of acceptance: January 25, 2013
Camera-Ready: February 8, 2013
Tutorials: June 4, 2013
Conference: June 5-7, 2013

The Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA) is an international event co-organised every two years, by the Portuguese and Spanish Associations for Pattern Recognition.

IbPRIA is a single track conference that includes tutorials, special sessions, invited speakers as well as oral and poster presentations. The conference intends to act as a forum for research groups, engineers and practitioners to present recent results, algorithmic improvements and promising future directions in pattern recognition and image analysis.

All accepted papers will be published in Springer Lecture Notes in Computer Science Series, Springer LNCS Series.

A short list of presented papers will be selected so that revised and extended versions of these papers will be published in a special issue of the Neurocomputing journal.

SCOPE
The conference is looking for new theoretical results, techniques and main applications on any aspect of pattern recognition and image analysis, including but not restricted to the following topics:
Pattern Recognition
Image Analysis
Computer Vision
Multimedia Systems
Statistical and Structural Pattern Recognition
Machine Learning and Data Mining
Computer Vision for Robotics and Automation
Bioinformatics
Image Coding and Processing
Shape and Texture Analysis
Information Systems
Biometric Technologies
Speech Recognition
Document Processing
Character and Text Recognition
Robotics
Remote Sensing
Industrial Applications of Pattern Recognition
Special Hardware Architectures

PAPER SUBMISSION
Papers should describe original and unpublished work on the topics of the conference. Prospective authors should prepare a full paper, written in English, not exceeding 8 pages and must submit it electronically. Further information can be found on the conference website: http://www.ibpria.org/2013.
Each paper will be blind-reviewed by at least two reviewers and will be accepted based on its originality, significance and clarity. All accepted papers will appear in the conference proceedings, and will be published in Springer Lecture Notes in Computer Science Series, Springer LNCS Series. A copy of the proceedings will be distributed to all participants at the Conference.
A short list of presented papers will be selected so that revised and extended versions of these papers will be published in the Neurocomputing journal.

Submission implies that at least one of the authors has to register and to present the communication at the conference if the paper is accepted.

IMPORTANT DATES
Submission of papers: November 30, 2012
Notification of acceptance: January 25, 2013
Camera-Ready: February 8, 2013
Tutorials: June 4, 2013
Conference: June 5-7, 2013

For more information please visit http://www.ibpria.org/2013

Two salaried PhD positions in Machine Translation at Sheffield University – Marie Curie ITN project EXPERT

Applications are invited for two 3-year Early Stage Researcher PhD positions in corpus-based approaches to machine translation. The positions have been awarded as part of the new EU FP7 Marie-Curie Initial raining Network EXPERT (http://clg.wlv.ac.uk/projects/EXPERT/), concerned with the exploitation of empirical approaches to machine translation, including statistical machine translation and example-based machine translation. The EXPERT project puts together researchers from six European universities (The University of Sheffield, Universidad de Malaga, Universitaet des Saarlandes, Dublin City University, Universiteit van Amesterdam, and University of Wolverhampton) and five translation services and technology providers (Pangeanic, Hermes and Translated, Celer Soluciones and WordFast).
The two projects allocated to the University of Sheffield are (i) learning from human feedback, which is concerned about methods to collect and incorporate human feedback into translation systems to improve the quality of translations; and (ii) estimating the quality and confidence of corpus-based approaches to machine translation and the quality of translated texts.
The work in both projects will focus on statistical and machine learning techniques to address the problems, but it will also involve aspects of human translation studies, based on a strong interaction with some of the partners in EXPERT. The research will be conducted as part of the Natural Language Processing research group in Sheffield, with opportunities for collaborative work with several of the leading universities and industrial partners in EXPERT, and with the expectation of a 6-month secondment to 2-3 partners in this project. Further information about the research group can be found at: http://nlp.dcs.shef.ac.uk
The successful individual will be employed as a salaried researcher at the University of Sheffield, while studying towards his/her PhD. Salary rates and additional mobility and training allowances are as per the Marie Curie programme (see Annex 3 of this document http://ec.europa.eu/research/participants/portal/download?docId=31562, page 69). For employment in the UK, the reference figure for gross salary is 51,062 euros/year, plus additional contribution towards mobility and training.
Please check Section III.3 of the following link for further information on the Marie Curie scheme regarding eligibility criteria: ftp://ftp.cordis.europa.eu/pub/fp7/docs/fp7-mga-annex3intramulti_en.pdf. In particular, candidates cannot have lived in the UK for more than 12 months in the 3 years immediately prior to their appointment.
Applicants should hold a good honours degree in a relevant field of study (e.g. computer science, engineering, mathematics) and have experience in natural language processing, machine translation or related area. They should also have a solid background in mathematics/statistics and excellent programming skills (C/C++, Java, Python/Perl, etc.). See the job specification for more details on the expected profile: http://www.dcs.shef.ac.uk/~lucia/resources/EXPERT_Marie_Curie_Early_Stage_Researcher.pdf
The post is fixed term for three years with a start date of January 2013 or soon after.
Closing Date: 10th December 2012

For applications: http://www.shef.ac.uk/jobs, Search and apply for jobs, job reference number: UOS005598
In addition to submitting applications to the University of Sheffield, candidates should apply via the website provided by project coordinator: http://clg.wlv.ac.uk/projects/EXPERT/.

For informal enquiries about this job and department, contact: Dr Lucia Specia on l.specia@sheffield.ac.uk