Postdoc position in “Machine Learning and Functional Data Analysis for Structured Output Prediction”

We are looking for a strongly motivated person with a PhD degree, and a good background in machine learning (ML) with experience in kernel methods, time series analysis and/or structured prediction, for a 1 year postdoctoral position at LIF. The candidate will work within the framework of a project of the French National Research Agency: ANR
Lampada: Learning Algorithms, Models and sPArse representations for structured DAta.

The selected candidate will join the Fundamental Computer Science laboratory (Laboratoire d’Informatique Fondamentale de Marseille, a.k.a.
LIF – Marseille, France) and will work, in collaboration with the Qarma (Machine Learning and Multimedia) team. He/she will be involved in developing new theoretical and algorithmic approaches to (nonparametric) ML methods and exploring their use for applications involving functional or/and structured data. Knowledge on functional data analysis (FDA) techniques will be appreciated. Additional information about QARMA can be found at http://www.lif.univ-mrs.fr/~qarma/.

The postdoc will be working directly with Hachem Kadri and François Denis within the QARMA team, and will have the opportunity to collaborate with other members of a research group of IBISC specialized in Machine Learning in Systems Biology, including Florence d’Alché-Buc.

The position is expected to be available starting January 2013.
Applications will be continuously received until the position is filled.

Applications and further questions regarding the position should be addressed to hachem.kadri@lif.univ-mrs.fr and francois.denis@lif.univ-mrs.fr. For more information, see http://www.lif.univ-mrs.fr/~qarma/?q=content/postdoc-position-available.

If you are planning to go to NIPS this year, we could set up an appointment there.

ESANN 2013: CFP and special sessions

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/

Call for papers and special sessions
======================================================

Deadline for submission of papers:
———————————-
30 November 2012

Topics
——
Machine learning, artificial neural networks, computational intelligence and related topics (see below for a more detailed description of the conference topics).

Special sessions
—————-
(see http://www.esann.org/ for abstracts):
1) Machine Learning Methods for Processing and Analysis of Hyperspectral Data
Andreas Backhaus (a), Marika Kästner (b), Udo Seiffert (a), Thomas Villmann (b), (a) Fraunhofer IFF Magdeburg, (b) Univ. of Applied Sciences Mittweida (Germany)

2) Developments in kernel design
Lluís A. Belanche , Universitat Politècnica de Catalunya (Spain)

3) Human Activity and Motion Disorder Recognition: towards smarter Interactive Cognitive Environments
Jorge Luis Reyes-Ortiz (a,b), Alessandro Ghio (a), Xavier Parra-Llanas (b), Davide Anguita (a), Joan Cabestany (b), Andreu Català (b), (a) University of Genoa (Italy), (b) Universitat Politècnica de Catalunya (Spain)

4) Missing Data in Machine Learning and Statistical Learning
Christophe Biernacki , Vincent Vandewalle , INRIA (France), Yoan Miche , Emil Eirola , Aalto University (Finland), Amaury Lendasse , Ikerbasque (Spain), Eric Severin , University of Lille I (France)

5) Machine Learning for multimedia applications
David Picard , ETIS – ENSEA, Philippe-Henri Gosselin , INRIA Rennes (France)

6) Sparsity for interpretation and visualization in inference models
Vanya Van Belle, (a,b), Paulo Lisboa, (b), (a) Katholieke Universiteit Leuven (Belgium), (b) Liverpool John Moores University (UK)

Scope and topics
—————-
Since its first happening in 1993, the European Symposium on Artificial Neural Networks has become the reference for researchers on fundamentals and theoretical aspects of artificial neural networks, computational intelligence, machine learning and related topics. Each year, around 100 specialists attend ESANN, in order to present their latest results and comprehensive surveys, and to discuss the future developments in this field.

The ESANN 2013 conference will follow this tradition, while adapting its scope to the recent developments in the field. The ESANN conferences cover artificial neural networks, machine learning, statistical information processing and computational intelligence. Mathematical foundations, algorithms and tools, and applications are covered.

The following is a non-exhaustive list of machine learning, computational intelligence and artificial neural networks topics covered during the ESANN conferences:

THEORY and MODELS
Statistical and mathematical aspects of learning
Feedforward models
Kernel machines
Graphical models, EM and Bayesian learning
Vector quantization and self-organizing maps
Recurrent networks and dynamical systems
Blind signal processing
Ensemble learning
Nonlinear projection and data visualization
Fuzzy neural networks
Evolutionary computation
Bio-inspired systems

INFORMATION PROCESSING and APPLICATIONS
Data mining
Signal processing and modeling
Approximation and identification
Classification and clustering
Feature extraction and dimension reduction
Time series forecasting
Multimodal interfaces and multichannel processing
Adaptive control
Vision and sensory systems
Biometry
Bioinformatics
Brain-computer interfaces
Neuroinformatics

Papers will be presented orally (single track) and in poster sessions; all posters will be complemented by a short oral presentation during a plenary session. It is important to mention that the topics of a paper decide if it better fits into an oral or a poster session, not its quality. The selection of posters will be identical to oral presentations, and both will be printed in the same way in the proceedings. Nevertheless, authors must indicate their preference for oral or poster presentation when submitting their paper.

Location
——–
The conference will be held in Bruges (also called “Venice of the North”), one of the most beautiful medieval towns in Europe. Bruges can be reached by train from Brussels in less than one hour (frequent trains). The town of Bruges is world-wide known, and famous for its architectural style, its canals, and its pleasant atmosphere.

The conference will be organized in a hotel located near the centre (walking distance) of the town. There is no obligation for the participants to stay in this hotel. Hotels of all levels of comfort and price are available in Bruges; there is a possibility to book a room in the hotel of the conference at a preferential rate through the conference secretariat. A list of other smaller hotels is also available.

The conference will be held at the Novotel hotel, Katelijnestraat 65B, 8000 Brugge, Belgium.

Proceedings and journal special issue
————————————-
The proceedings will include all communications presented to the conference (tutorials, oral and posters), and will be available on-site. Extended versions of selected papers will be published in the Neurocomputing journal (Elsevier).

Call for contributions
———————-
Prospective authors are invited to submit their contributions before November 30, 2012. The electronic submission procedure is described on the ESANN website http://www.esann.org/.

Authors must also commit themselves that they will register to the conference and present the paper in case of acceptation of their submission (one paper per registrant). Authors of accepted papers will have to register before February 28, 2013; they will benefit from the advance registration fee. The ESANN conference applies a strict policy about the presentation of accepted papers during the conference: authors of accepted papers who do not show up at the conference will be blacklisted for future ESANN conferences, and the lists will be communicated to other conference organizers.

Deadlines
———
Submission of papers 30 November 2012
Notification of acceptance 1 February 2013
ESANN conference 24-26 April 2013

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

* 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
========================================================

Several Postdoc / Research Associate positions in the Finnish Center of Excellence in Computational Inference

Keywords: Machine learning, computational statistics, Bayesian
statistics, information-theoretic learning, satisfiability checking,
proactive interfaces, computational biology

The Finnish Center of Excellence in Computational Inference Research
(COIN), run by Aalto University, University of Helsinki, and Helsinki
Institute for Information Technology HIIT, announces several new
postdoc or research associate positions in Computational
Inference. The objective of COIN is to push the boundaries of
inference in the data-rich world of today and tomorrow, and the COIN
consortium brings together several leading researchers in the relevant
research areas.

Successful candidates will work on fundamental questions of inference
and in applications in Intelligent Information Access, Computational
Molecular Biology and Medicine, Computational History, Computational
Climate, Computational Neuroscience or other directions yet to be
determined. Applicants with suitable background in machine learning,
mathematics, statistics, computational logic, combinatorial optimization
or statistical physics are encouraged to apply.

For further information, please see
http://research.ics.tkk.fi/coin/vacancies.shtml

Ph.D. vacancy at the School of Computing Science, University of Glasgow, supervised by Prof. Roderick Murray-Smith

Available immediately, part-funded and run in collaboration with Bang & Olufsen ( http://www.bang-olufsen.com ). There will be opportunities for internships at Bang & Olufsen’s labs in Denmark during the Ph.D.

Natural Interaction with Products
Living rooms now contain a large number of different sensors and interactive surfaces. The Microsoft Kinect can detect movements and voice, a multitude of different sensors that can detect movements, presence, identity, voice, etc. are now widely available and TVs have video cameras and microphones that detect gestures and voice commands. Input and output are spread across many different devices with different capabilities and accuracies.

Based on this it is relevant to study how best to take advantage of the various technologies in the best possible way when creating interactive products. Areas of research in this project are include: 1. Combining sensing for precise positioning and control – A wide range of sensors are available in the living room context. 2. Modality scheduling – if we can improve positioning and gesture recognition, how should we give feedback to users at each stage of the interaction? Which sensors or channels dominate might be different at different points in the interaction. Combining multi-sensor input with multimodal feedback we can then investigate the best ways of closing the loop between input and output in the context of the living room.

The stipend funding is at standard UK rates (£13,590), which are usually tax-free, and the project also includes fees for EU citizens. Please apply ASAP to Roderick.Murray-Smith@glasgow.ac.uk
http://www.dcs.gla.ac.uk/~rod/

Post-doctoral position in Computational Metagenomics of Deep Biosphere (DL Nov 15) – Aalto

http://www.aalto.fi/en/current/jobs/teaching_and_research/deep_biosphere_postdoc/

The Department of Information and Computer Science at Aalto University in Espoo/Helsinki, Finland, pursues research on advanced computational methods for modelling, analysing, and solving complex tasks in technology and science. The research aims at the development of fundamental computer science methods for the analysis of large and high-dimensional data sets, and for the modelling and design of complex software, networking and other computational systems.

The geobiology research consortium at Biotechnology cluster of VTT (www.vtt.fi) in Espoo/Helsinki Finland is studying terrestrial deep biosphere. The research is connected to biogeochemistry and microbial ecology of deep earth crust ecosystems. Metadata and metapathway analysis of multispecies microbial communities will be studied in collaboration with multidiscicplinary research team of Aalto University and VTT.

We are looking for a motivated, self-driven post-doctoral researcher to join our multidisciplinary research team deciphering the metagenomics and meta-transcriptomics of deep earth crust microbial communities.

Research is connected to ICDP (International Continental Scientific Drilling Program) and global network of Deep carbon observatory (https://dco.gl.ciw.edu/) as well as the National Centre of Excellence on Algorithmic Data Analysis.

We expect the applicants to have a PhD (or to have submitted a dissertation for evaluation) in Computer Science, Statistics, Computational Biology, Bioinformatics or a related field, with excellent publication record and expertise in one or more of the following fields:
• Next generation sequencing
• Algorithm design
• Machine learning and data mining
• Systems biology

Excellent programming (Python, MATLAB, R) and technical skills, as well as excellent written and oral communication skills are required. Previous expertise in metagenomics data analysis or metabolic modelling is considered an advantage. In addition to research work, a postdoctoral researcher is expected to participate in the supervision of students and teaching related to their research topic. Good command of English is a necessary prerequisite.

The successful candidate will join a team of researches led by Docent Merja Itävaara (VTT Technical Research Centre of Finland) and Professor Juho Rousu (Aalto University and Helsinki Institute for Information Technology). The post doc position is for two years and is jointly affiliated with both VTT and Aalto University.

Application procedure
The applications should be sent by email to registry@aalto.fi and they should contain the following documents in pdf format:

• Expression of interest that includes contact information of the applicant, and names and contact information of two senior academics available for reference per e-mail.
• A complete curriculum vitae describing education and employment history
• List of publications, with pointers to openly available online versions of at most three of the most relevant publications Please use “DeepBiosphere” as a reference in the application. Applications received by November 15, 2012 will receive full consideration.

The salary level for a starting postdoctoral researcher is between 3200 and 3600 euros per month, depending on experience and qualifications. The contract includes occupational health services and Finland has a comprehensive social security system. Candidates may be invited for an interview on the Otaniemi campus of Aalto University in Espoo/Helsinki.

For further information, please contact:

Professor Juho Rousu
Department of Information and Computer Science, Aalto University PO Box 15400 (Konemiehentie 2, Espoo), 00076 Aalto, Finland Firstname.lastname@aalto.fi

Docent Merja Itävaara
VTT Technical Research Center of Finland Tietotie 2, 02044 VTT, Finland Firstname.lastname@vtt.fi

About the Department of Information and Computer Science In the recent Research Assessment Exercise covering all the 46 units of Aalto University, the Department of Information and Computer Science was one of two units achieving an almost perfect score of 24 out of 25, from review panels assessing the units on a scale of 1 to 5 in the five subareas of scientific quality, scientific impact, societal impact, research environment, and future potential. For more information about the Department’s research profile and activities, see the full RAE report available at “http://dept.ics.aalto.fi/calls/rae2009/“.

About Aalto University
Aalto University is a new university created in 2010 from the merger of the Helsinki University of Technology TKK, the Helsinki School of Economics, and the University of Art and Design Helsinki. The University’s cornerstones are its strengths in education and research, with 20,000 basic degree and graduate students, and a staff of 4,500 of whom 300 are professors. For further information, see http://www.aalto.fi/en

About VTT
VTT Technical Research Centre of Finland is an impartial expert organisation. Its objective is to develop new technologies, create new innovations and value added thus increasing customer’s competitiveness. With its know how VTT produces research, development, testing and information services to public sector and companies as well as international organisations. Through its international scientific and technology network, VTT can produce information, upgrade technology knowledge, create business intelligence and value added to its stakeholders. VTT is a non-profit-making research organisation.

Research Associate in Statistics for Natural Hazards, – Ref:1288815

Applications are invited for the position of Research Associate, to be
held jointly in the UCL Department of Statistical Science and Institute
for Risk and Disaster Reduction. The postholder will conduct research in
Statistics related to the £2m interdisciplinary consortium RACER (Robust
Assessment and Communication of Environmental Risk) funded by the
Probability, Uncertainty and Risk in the Environment (PURE) program of
the Natural Environment Research Council (NERC). The research will focus
in particular on models for seismic and tsunami hazards and involves
using state-of-the-art statistical methodology for uncertainty
assessment and calibration of computer codes.

Candidates should hold or be close to completing a PhD (or equivalent
qualification) in statistical methodology or applied statistics. It is
essential that the successful candidate will have experience of Bayesian
methods and uncertainty quantification of complex computer models.

The post is available from January 2013 (or as soon as possible
thereafter) and is initially funded for 36 months. Salary (inclusive of
London allowance) will be Grade 7 of the UCL salary scale
(32,055-33,826GBP per annum). If the successful candidate has not yet
been awarded their PhD, the appointment will initially be made as
Research Assistant on Grade 6 (28,057-29,585GBP per annum), and the
appointee will be regraded to Research Associate on completion of the PhD.

Further particulars including a job description and person specification
for the post can be accessed at
http://www.ucl.ac.uk/statistics/department/jobs. Informal inquiries
regarding the vacancy may be addressed to Dr Serge Guillas,
email:s.guillas@ucl.ac.uk, tel: +44(0)20 7679 1867. For any queries
regarding the application process please contact Dr Russell Evans,
email:russell.evans@ucl.ac.uk, tel: +44 (0)20 7679 8311.

Closing Date: 3 December 2012

Statistical Physics of inference and control videolectures

Dear friends and colleagues,

It is a great pleasure to announce the video lectures of the recent Workshop on the Statistical Physics of inference and control that was
held from 12-16 september in Granada, Spain. The workshop is the first of its type explore the relations between stochastic optimal control theory, machine learning, robotics, statistical mechanics, quantum theory and the theory of large deviations.

The workshop was made possible in part by support from Pascal 2.

Enjoy watching: http://videolectures.net/cyberstat2012_granada/

Apologies for multiple posting.

Bert Kappen
Riccardo Zecchina
Misha Chertkov
Frank Redig

Postdoctoral Research Fellow Positions in machine learning and data mining at KAUST

Appointments Available Immediately

Job Description

Two Postdoctoral Research Fellow positions are available in Machine Intelligence and Knowledge Engineering (MINE) Laboratory directed by Dr. Xiangliang Zhang in the Division of Computer, Electrical and Mathematical Sciences & Engineering (CEMSE) at King Abdullah University of Science and Technology (KAUST) located on Red Sea shore. Candidates with experience in one or more of the following research areas are invited to apply: machine learning, data mining, databases, information retrieval and recommender systems. More information about MINE Lab can be found at http://mine.kaust.edu.sa.

Candidates need to hold an earned Ph.D. (or be near completion) in computer science or in a related field with good programming skills in C/C++/Java/Matlab. Successful candidates are expected to be self-motivated and have a good publication record (at least have one paper accepted by premier conferences or journals like KDD, NIPS, ICML, IJCAI, AAAI, SIGMOD, VLDB, ICDE, WWW, SIGIR, TKDE, TKDD, etc.) and good command of English. The position holders will perform interdisciplinary research, shape research directions, produce and disseminate results through publications, coordinate research projects and help to supervise Ph.D. and M.S students.

The PostDoc positions are for 1 to 3 years.

KAUST offers

-Very competitive tax exemption salary and benefit package (e.g., free high-standards fully furnished houses, health insurance, education at KAUST international schools for children, 20 days of paid vacation per year, relocation allowance, repatriation allowance).
– Sufficient funding support (e.g., conference attendance and international trip support).
– State-of-the-art research facilities, including one of the fastest supercomputers in the world (IBM BlueGene, 64000 cores, 64TB RAM), and a word-class visualization center.
– Solid collaboration (including exchange visits) with our partners such as IBM T.J. Watson Research Center, Texas A&M University, INRIA, Microsoft Research Asia and others.
-Vibrant campus life and impressive recreational facilities that include a private beach, marina and golf course.

Application

Eligible and interested applicants are invited to submit their application electronically to Dr. Xiangliang Zhang (xiangliang.zhang@kaust.edu.sa) with a detailed professional Curriculum Vita (including educational background, professional experience, and a list of publications). Successful candidates will be further contacted to provide more documents (e.g., two or three recommendation letters and a brief statement of research interests/plans).

Applications will be handled in strict confidentiality. KAUST is an equal opportunity employer.

Deadline: Review of applications will begin immediately and the positions will remain open until filled.

About KAUST

King Abdullah University of Science and Technology (KAUST) is a brand new, international, graduate-level research university supported by a multi-billion dollar endowment. With sufficient research funding, highly competitive and merit-based compensation scheme, state-of-art core facilities, supercomputing machines (for KAUST’s Shaheen Supercomputer see http://www.hpc.kaust.edu.sa/) and university leadership’s vision and commitment to make KAUST one of the world’s greatest academic institutions, KAUST has attracted a large group of internationally recognized talents. Joint (PhD) Degree Program will shortly be released between KAUST and Technische Universität München (TUM), and TA&M, and Graduate University of Chinese Academy of Sciences. Furthermore, through a Global Research Partnership, KAUST has built up deep and meaningful partnerships with the world’s most premier institutions (e.g., Stanford University, University of Illinois at Urbana Champaign (UIUC), The University of Oxford, UC Berkeley, Cornell University, University of Texas at Austin, Texas A&M University) and big companies (e.g., IBM, Boeing, Dow Chemical Company), which provide KAUST researchers ample opportunities to work with the world’s most leading scientists and to commercialize their research projects. The aforementioned unrivaled resources available to KAUST researchers offer unprecedented opportunities for scientists from around the globe and across all cultures to build up their career at KAUST. Further information about KAUST can be found at: http://www.kaust.edu.sa.

Postdoc positions in ML & Robotics at University Stuttgart

*Postdoc Positions at the new*
*Machine Learning & Robotics Lab, Stuttgart*

Two Postdoc positions are available at the new Machine Learning & Robotics which will be launched at University Stuttgart in January 2013. The lab focuses on the intersections between Machine Learning (Reinforcement Learning) and Robotics, covering topics such as the combination of logic, probabilities and geometry; representation and symbol learning for acting; probabilistic inference for control and planning; and autonomous exploration. Post docs with either more affinity to Robotics (e.g., building autonomous systems that learn via exploration, imitation or instruction) or Machine Learning (e.g., addressing core challenges as mentioned above in the context of RL or
perception) are equally invited to apply.

The available positions range from senior group leader level (A14, potentially unlimited contract) to short term Postdoc, depending on your profile and plans. The lab offers rich infrastructure (e.g., we plan to get a PR2) and close proximity and cooperation possibilities with the Max-Planck Institute for Intelligent Systems (Schölkopf, Schaal, Black). Senior Postdocs have one or more PhD positions, depending on additional funding.

The application process is informal. Applicants should have an excellent publication record on the relevant conferences (e.g., RSS, ICRA, IROS or ICML, UAI, NIPS, AISTATS) and in these publications demonstrate genuine and methodologically solid research ideas and superior knowledge of their field. In you have any questions concerning the position, please contact me any time informally.

Applications should be send by email to marc.toussaint@fu-berlin.de, including a pointer to your webpage where publications can be downloaded, and an ordinary CV. There is no fixed deadline: positions will be open until appropriate candidates are found (at least until Oct 22nd). Please contact me on your earliest convenience.

Best,
Marc

—
Marc Toussaint, Prof. Dr.
FU Berlin
Arnimallee 7
14195 Berlin, Germany
+49 (0)30 838 52485
http://userpage.fu-berlin.de/~mtoussai/

PhD Studentship ­in computer vision/machine learning at CVSSP

Learning Deep Hierarchical Visual Representations PhD Studentship ­ CVSSP, University of Surrey (http://www.surrey.ac.uk/cvssp/), UK.

We are looking for a PhD student to study the development of novel, multi-purpose representations of visual information making use of hierarchical and distributed encoding and weakly supervised learning approaches. The candidates are expected to have solid programming experience and mathematical background, and a broad interest in vision and cognition problems is desirable.

Successful applicants will join an expanding research group within the Centre for Vision Speech and Signal Processing which has over 120 people working in vision, machine learning and related disciplines. It has an international reputation for the excellence of its research and, in the last Research Assessment Exercise; the Department (of Electronic
Engineering) was rated as second in the country with the highest return of staff for any institution.

Candidates should hold a 1st or strong 2.1 honours degree or Masters degree or equivalent in a scientific discipline (e.g., Engineering, Physics, Mathematics or Computing), and should have good written/spoken English and demonstrate an aptitude for the research area. Prior experience in computer vision, image processing or machine learning would be advantageous.

The position would be starting in January 2013 or as soon as possible after that date. Applicants should send a CV and covering letter to Dr.
Pugeault (n.pugeault@surrey.ac.uk) before the 15th of November. For further information please contact Dr. Nicolas Pugeault (http://info.ee.surrey.ac.uk/Personal/N.Pugeault/)