Postdoc/PhD student for computational genetics (1,0 fte)
Advert available at http://www.snn.ru.nl/nijmegen/index.php?option=com_content&view=article&id=54&It
Advert available at http://www.snn.ru.nl/nijmegen/index.php?option=com_content&view=article&id=54&It
PhD Position in Biomedical Data Analysis at the University of Basel, Switzerland
Applications are invited for a PhD position in the Biomedical Data Analysis Group at
the Department of Computer Science of the University of Basel.
The open position is part of the “SINERGIA”-research project “Emotional Memory in
Health and Disease” funded by the Swiss National Science Foundation.
This interdisciplinary research effort aims at identifying the molecular genetic basis of
emotional memory by combining experimental, clinical, and computational approaches.
The position involves development of computational methods for genome-wide
association studies, statistical analysis of gene interactions, computational modeling of
disease-related gene regulatory pathways, as well as data integration and human-mouse
comparative data analysis.
Successful applicants have a profound knowledge in mathematical modeling and in
algorithmics. Furthermore, the project requires substantial programming skills and a
genuine interest in computational biology. Candidates are expected to engage in
interdisciplinary research groups and to foster collaborations with clinicians and
biologists.
A prerequisite is a Masters degree in Computer Science, Bioinformatics, Mathematics or
Physics.
For further inquiries, please contact
Volker Roth, Email: volker.roth(at)unibas.ch
Phone: +41-61-2670549
Successful candidates will be awarded a fellowship with a competitive salary (~43000
CHF/year).
Applications with a full CV, list of publications, short statement of research interests
and names of at least one referee should be submitted (in electronic form) to
volker.roth(at)unibas.ch
6th International Summer School and Workshop on Pattern Recognition (5-10 September, 2010)
Registration is now Open – take advantage of early registration fee
The International Summer School on Pattern Recognition is the premier event on research training in the area of pattern recognition and machine learning. The school is fully residential and its registration includes all attendance, and living costs. The vision of the summer school is to empower its participants with the state-of-the-art techniques in pattern recognition and machine learning – to provide a deep understanding of how techniques work, their strengths and limitations, and the future of things to come in this field.
If you have used or will use pattern recognition technology, this is a must attend event. You can:
– Learn from leading experts in pattern recognition and machine learning on a range of topics including statistical pattern recognition, Bayesian approaches, structural approaches, neural networks and support vector machines, data mining, classification, evolutionary computation, markov models, feature selection and reduction, and many more.
– Demonstrate your research till date and win best research prizes sponsored by Microsoft. The event is supported by Microsoft Research, Springer, and Mathworks.
– Meet some of the leading exponents in pattern recognition and machine learning area, network with your peers from around the world using similar tools to solve complex problems
– Enjoy a unique learning experience within a fully residential summer school, admired by previous participants as one of the best summer schools available
www.patternrecognitionschool.com
Email for enquiries: m.singh(at)lboro.ac.uk, or enquiries(at)patternrecognitionschool.com
Human-observer based methods for measuring human motion are labor intensive qualitative, and difficult to standardize across laboratories, clinical settings, and over time. Moreover, many conditions that affect normal human movements are currently diagnosed during short visits to the clinician. Advances in wearable and wireless sensor networks have opened up new opportunities in health care systems. We are looking for a postdoc to develop novel machine learning algorithms able to perform medical diagnosis, temporal segmentation and activity recognition from accelerometer data. To qualify for the position, it is mandatory to have research experience in time series analysis. A proven record of publications in top machine learning conferences and journals is required. This will initially be a one year position with the possibility of an extension pending funding.
To apply: Applications should be sent by email to jkh(at)cs.cmu.edu and ftorre(at)cs.cmu.edu . It should include a CV, a brief statement of research interests, the expected date of availability and the names for 3 references. Applications should be sent as soon as possible and preferably before July 20th, 2010, but later applications may be considered until the position is filled.
The 5th International Conference on Pervasive Computing and Applications
(ICPCA 2010)
CALL FOR PAPERS
http://icpca.lzu.edu.cn/
Maribor, Slovenia December 1-3, 2010
The ICPCA steering committee cordially invites you to submit a paper to the 5th International Conference on Pervasive Computing and Applications, held in Maribor, Slovenia, between 1 and 3 December, 2010.
Sponsors:
* Microsoft
* HP
* SRA
* IEEE
Topics:
* Mobile and Wireless Networks and Communications
* Semantic technologies in Pervasive Computing
* Context-awareness
* Data Grid and Data Cloud
* Distributed data and knowledge management
* Distributed intelligence
* Innovative HCI Technologies
* Socio-technical Issues in Pervasive Computing
* Applications and case studies
ICPCA2010 extends its interests in pervasive computer with special tracks on collaborative work, health care, e-learning, emergency management, security, etc. In addition to technical papers, ICPCA2010 will include keynote speeches, penal discussions, late breaking results, and demonstrations.
Submission of Papers:
All papers must be unpublished and should not be under simultaneous review for any other conferences and workshops. Papers must be written in English and formatted according to the IEEE conference proceedings. Research papers should be no more than 6 pages including references and illustrations. Position papers and system demos are also welcome. Electronic submissions in PDF or PS format are recommended.
Important Dates:
* Technical paper
Deadline for submission 30/07/2010 (extended)
Notification of acceptance 15/09/2010
Camera-ready deadline 15/10/2010
* System demo/position paper/etc.
Deadline for submission 01/09/2010
Notification of acceptance 15/09/2010
Camera-ready deadline 15/10/2010
This conference is sponsored by IEEE Slovenia Section and Lanzhou University. All papers accepted will be indexed by EI. For more information, please contact us:
ICPCA Organising Committee
icpca10(AT)easychair.org
We are delighted to announce an updated release of the GPML Toolbox.
The code as well as the documentation and a tutorial can be obtained from
http://www.gaussianprocess.org/gpml/code
The GPML toolbox implements approximate inference algorithms for
Gaussian processes such as Expectation Propagation, the Laplace
Approximation and Variational Bayes for a wide variety of likelihood
functions for both regression and classification. It comes with a large
algebra of covariance and mean functions allowing for flexible
modeling.
Requirements: octave 3.2.x or matlab 7.x
Platform: any, tested on: mac, linux and windows
License: FreeBSD
Carl Edward Rasmussen & Hannes Nickisch
The Machine Learning for Optimisation and Services group (MLS) at Xerox Research Centre Europe is expanding. We conduct fundamental research in statistical machine learning and algorithmic mechanism design, with applications to abstract knowledge representation, content creation, recommendation systems and dynamic pricing. Our research is the result of combining state-of-the-art expertise in computational linguistics, large-scale data mining, computational statistics and game theory.
We are currently looking for two very strong researchers in the following areas:
1. Statistical Machine Learning for Text Understanding and Multi-document Summarisation:
www.xrce.xerox.com/About-XRCE/Career-opportunities/Research-Scientist-in-Statistical-Machine-Learning-for-Text-Understanding-and-Multi-document-Summarisation
2. Statistical Machine Learning and Algorithmic Mechanism design:
www.xrce.xerox.com/About-XRCE/Career-opportunities/Research-Scientist-in-Machine-learning-and-Algorithmic-Mechanism-Design
Applicants will have to demonstrate their capacity to define and/or implement research plans, to carry out leading research through collaboration with Xerox researchers and also the wider academic community. As a researcher you will be expected to formalize challenging problems, develop new solutions, and work with business and development teams to ensure that these solutions have a significant impact. We work together with top academic partners and expect our researchers to publish results in top-tier conferences and journals.
Requirements:
– PhD in Statistics, Mathematics, Economics or Computer Science
– Strong publication record in top tier conferences and journals
– Evidence of implementing systems
– Strong English-language written and oral communications skills
The application deadline is August 15, 2010. Applications will be considered after this date until the positions are filled.
Informal inquiries can be made to Cedric.Archambeau(AT)xerox.com, Guillaume.Bouchard(ATxerox.com or Onno.Zoeter(AT)xerox.com. To submit an application, please send your CV and cover letter to both xrce-candidates(AT)xrce.xerox.com and the aforementioned email addresses. You should also include in your CV at least three referees we can contact for letters of recommendation.
PhD Position in Biomedical Data Analysis at the University of Basel, Switzerland
Applications are invited for a PhD position in the Biomedical Data Analysis Group at
the Department of Computer Science of the University of Basel.
The open position is part of the research project “Emotional Memory in Health and
Disease” funded by the Swiss National Science Foundation.
This interdisciplinary research effort aims at identifying the molecular genetic basis of
emotional memory by combining experimental, clinical, and computational approaches.
The position involves development of computational methods for genome-wide
association studies, statistical analysis of gene interactions, computational modeling of
disease-related gene regulatory pathways, as well as data integration and human-mouse
comparative data analysis.
Successful applicants have a profound knowledge in mathematical modeling and in
algorithmics. Furthermore, the project requires substantial programming skills and a
genuine interest in computational biology. Candidates are expected to engage in
interdisciplinary research groups and to foster collaborations with clinicians and
biologists.
A prerequisite is a Masters degree in Computer Science, Bioinformatics, Mathematics or
Physics.
For further inquiries, please contact
Volker Roth, Email: volker.roth@unibas.ch, Phone: +41-61-2670549
Successful candidates will be awarded a fellowship with a competitive salary (~43000
CHF/year).
Applications with a full CV, list of publications, short statement of research interests
and names of at least one referee should be submitted (in electronic form) to
volker.roth@unibas.ch
MEDIA RETARGETING WORKSHOP
in conjunction with ECCV 2010, September 10, Crete, Greece
http://www.vision.ee.ethz.ch/MRW2010
OVERVIEW
Media retargeting is the process of adapting media content such as
images or video to the characteristics of different output devices.
Media retargeting has received considerable attention in computer
vision and graphics research in the recent years due to the growing
variability in capture devices and displays (small displays in mobile
devices, large high resolution displays in home cinema systems) and
the availability of huge amounts of image and video data. Besides
converting video between different display sizes, the spectrum of
problems related to media retargeting also comprises issues such as
color adaptation between different dynamic ranges, or the automatic
conversion of 2D to 3D footage for upcoming stereoscopic consumer
display devices.
The goal of this workshop is to bring together researchers and
practitioners from all areas of computer vision, machine learning,
and computer graphics, and to stimulate the discussion about shared
concepts and recent progress on topics ranging from perceptual content
analysis over efficient optimization algorithms for retargeting to
systematic evaluation of already existing techniques.
CALL FOR PARTICIPATION
We invite high quality, original submissions for presentation during
the workshop. Contributions from the following areas are especially
welcome:
* video or image retargeting of aspect ratio and resolution
* color retargeting between low and high dynamic ranges
* visual saliency estimation
* attention estimation and perceptual metrics
* temporal retargeting and content summarization
* retargeting of stereoscopic content
* monocular video to stereo conversion
* relevant optimization techniques
* systematic evaluation and user studies of relevant methods
* perceptual studies of retargeting results
* multi-modal retargeting (e.g. video and sound)
DATES
* Full paper submission: June 16, 2010
* Notification of acceptance: July 9, 2010
* Camera ready version of accepted papers: July 13, 2010
KEYNOTE SPEAKER
* Ariel Shamir, Efi Arazi School of Computer Science, Herzliya
ORGANIZERS
* Thomas Deselaers, ETH Zurich
* Alexander Hornung, Disney Research Zurich
* Olga Sorkine, New York University
Two PhD Studentships
University of Surrey,
Centre for Vision, Speech and Signal Processing (CVSSP)
————————————————
Transfer learning for sports video understanding
CVSSP are offering an EPSRC funded 3 year PhD studentship in Computer
Vision within the area of Video Understanding and Transfer Learning. The
studentship covers UK/EU tuition fees plus a maintenance grant for three
years.
This PhD shall use video analysis techniques in order build an adaptable
system to provide high level description of game events. Most
importantly, the research will focus on transferring knowledge from one
game modality to another. Multiple cues shall be used. The student will
join a team of people who are already working on different aspects of
this problem, such as player action classification, ball event detection
and audio pattern recognition. This is part of the
ACASVA project (http://kahlan.eps.surrey.ac.uk/acasva/).
————————————————
Pose invariant face recognition
Face recognition is a challenging application for computer vision for a
number of reasons. First of all, faces in a general pose cannot be
easily registered in a consistent manner. Second, illumination tends to
play a dominating influence in assessing the similarity of two face
images. Third, uncontrolled pose often implies poor resolution, which
further complicates the face recognition problem. This PhD project will
tackle these problems with the help of a morphable 3D face model. By
fitting such a model to 2D face image, it should be possible to correct
the pose of the input image and perform the matching in a standard
frontal pose. More over, it should be possible to use the 3D model to
relight the query image to achieve photometric normalisation.
————————————————
Application procedure
Please send the completed Postgraduate Research Programmes application
form, available from www2.surrey.ac.uk/postgraduate/apply, to Prof J
Kittler by email to J.Kittler@surrey.ac.uk. Please address any enquiries
to Dr Teo de Campos at T.Decampos(at)surrey.ac.uk
The successful candidates will have strong mathematical background and
programming skills in C++. Research experience in Vision and Machine
Learning will be a plus.
CVSSP is part of the Faculty of Engineering and Physical Sciences, which
received the highest rating of 5**A in the 2001 Research Assessment
Exercise (RAE), and ranked 2nd in the 2008 RAE with the highest number
of research active staff.
Applicants are required to have a First Class (or good 2.1) Honours or
Masters Degree in a related discipline (for example, Electronic
Engineering or Computer Science). The successful candidate will receive
a studentship paying full “Home” (UK/EU) level fees, and a maintenance
grant for three years subject to satisfactory progress.
