University of Oxford faculty position in Machine Learning

UNIVERSITY LECTURER IN COMPUTER SCIENCE (MACHINE LEARNING) University of Oxford Department of Computer Science in association with Linacre College

The Department of Computer Science proposes to appoint a University Lecturer (US tenure-track assistant/associate professor equivalent) in Computer Science with effect from 1 May 2013 or a mutually agreed date prior to 1 October 2013. The successful candidate will be offered a Non-Tutorial Fellowship at Linacre College under arrangements described in the further particulars. The salary will be on a scale currently up to £57,581 per annum.

Applicants should hold a relevant PhD and have a demonstrated track record of research excellence in any area of theoretical or applied machine learning. Candidates are expected to have a strong track record of publication in leading machine learning venues (e.g. NIPS, ICML, JMLR etc.), or conferences and journals of relevant applied fields. Full details of the qualifications required and the duties of the post can be found in the further particulars.

The closing date for applications is Friday, 25th January 2013.

Queries about the post should be addressed in the first instance to Elizabeth Walsh at Elizabeth.walsh@cs.ox.ac.uk or telephone: +44 (0)
1865 283503.

Applications are particularly welcome from women and black and minority ethnic candidates, who are under-represented in academic posts in Oxford. The University is an Equal Opportunities Employer.

Further particulars for this position can be found at:
http://www.cs.ox.ac.uk/files/5254/ML_UL_Fin.pdf

i-like Opening workshop – 31 January 2013, 2:10pm to 5:30pm

Please go to http://www.i-like.org.uk/launch-day-31st-january-2013.html for details of this event.

The day is principally aimed at phd and post doc level, although others are more than welcome to attend as well.

Postdoc positions a KU Leuven, ESAT-SCD

The research group KU Leuven ESAT-SCD is currently offering 2 Postdoc positions (1-year, extendable) within the framework of the ERC Advanced Grant A-DATADRIVE-B http://www.esat.kuleuven.be/sista/ADB .

The research positions relate to the following possible topics:
-1- Prior knowledge incorporation
-2- Kernels and tensors
-3- Modelling structured dynamical systems
-4- Sparsity
-5- Optimization algorithms
-6- Core models and mathematical foundations
-7- Next generation software tool

The research group ESAT-SCD http://www.esat.kuleuven.be/scd/ at the university KU Leuven Belgium provides an excellent research environment being active in the broad area of mathematical engineering, including systems and control theory, neural networks and machine learning, nonlinear systems and complex networks, optimization, signal processing, bioinformatics and biomedicine.

The research will be conducted under the supervision of Prof. Johan Suykens. Interested candidates having a solid mathematical background and PhD degree can apply for these positions by sending their CV and motivation letter to johan.suykens@esat.kuleuven.be. For further information on these positions you may contact johan.suykens@esat.kuleuven.be.

AVSS-2013 Call for Workshop and Contest Proposals

AVSS-2013 Call for Workshop and Contest Proposals

10-th IEEE International Conference on
Advanced Visual and Signal-Based Surveillance

August 27-30, 2013 Krakow, Poland
http://www.avss2013.org

Workshop and contest proposals are being solicited for AVSS-2013. Workshops will take place on Aug. 27, 2013 prior to the start of the technical program of the conference.

The topic of the proposal should be related to the field of interest of AVSS community, namely surveillance based on various modalities including, but not limited to, visible light, infrared, mm-wave, audio, radio, etc., and in particular:

– Sensor-Centric Processing
– Data Management & Human-Computer Interaction
– Security and Privacy
– Processing, Detection, Tracking & Recognition
– Analytics, Situation Awareness & Decision Making
– Surveillance Systems and Applications

For a more detailed list of areas, please visit http://www.avss2013.org/call-for-papers

We particularly encourage workshops in the form of a contest targeting a task relevant to the conference areas of interest above. Papers published as part of the workshops will be included in the Conference proceedings and referenced by IEEE.

Details on workshop proposal submission procedure can be found at http://www.avss2013.org/call-for-workshops

Important Dates:

Workshop proposals due: February 18, 2013 Notification of workshop proposal acceptance: March 3, 2013 Workshop paper submission: Defined by workshop organizers Notification of workshop paper acceptance: Defined by workshop organizers Workshop camera-ready paper due: June 17, 2013

Workshops Chair
Jean-Marc Odobez,
Idiap research institute, Switzerland
odobez[at]idiap.ch

4 year phd position on stochastic optimal control theory for neural networks

In the context of the Marie Curie NETT project

http://www.neural-engineering.eu/

we have two 4 year PhD positions available in my research group in Nijmegen, the Netherlands.

See http://www.snn.ru.nl/nijmegen/index.php?option=com_content&view=article&id=54&Itemid=81

The aim of the work package is to build neural architectures for stochastic optimal control and learning. The research is motivated by the recent work on path integral control methods. For this class of control methods, the optimal control can be computed using sampling.
This approach has shown to be very effective for robotics and learning. The current project will address the question of how such control computations can be implemented in neural networks.

The project requires advanced expertise on neural networks, control theory and machine learning. The candidates are not required to have good knowledge of these fields at the start of the project, but are expected to learn these topics.
Candidates should have a completed academic degree in theoretical physics, mathematics or engineering. As part of our commitment to promoting diversity, we particularly encourage female candidates to apply. To comply with the mobility rules of the Marie Curie Actions, applicants must not have resided, worked or studied in the Netherlands for more than 12 months in the three years prior to September 2012.

For an overview of the research in my group see: www.snn.ru.nl/~bertk and www.snn.ru.nl

Two PhD positions in Computer Vision at the University of Edinburgh

University of Edinburgh
School of Informatics
Two PhD positions in Computer Vision

Applications are invited for two PhD students to work on a project funded by a European Research Council Starting Grant. The two main topics of interest are:

* continuously learn new object classes helped by the knowledge of classes learned before
* learning object classes from consumer videos

Applicants must have:

* Master degree in Computer Science or Mathematics
* Excellent programming skills (the project is in Matlab and C++)
* Solid mathematics foundations (especially algebra and statistics)
* Highly motivated
* Fluent in English, both written and spoken
* UK or EU nationality is mandatory
* Experience in computer vision and/or machine learning is a plus

The School of Informatics at Edinburgh is one of the top-ranked departments of Computer Science in Europe and offers an exciting research environment. Edinburgh is a beautiful historic city with a high quality of life.

Starting date: January 2013 or later

The PhD work will be carried out under the supervision of Dr. Vittorio Ferrari. For an overview of current research activities, please visit

http://groups.inf.ed.ac.uk/calvin/

For pre-screening, please send applications to the email address below, including:
* complete CV
* title and abstract of master thesis
* complete grades for all exams passed during both the bachelor and master
(to obtain this position you need high grades, especially in mathematics and programming disciplines)
* the name and email address of one reference (preferably your master thesis supervisor)
* if you already have research experience, please include a publication list

email: vferrari@staffmail.ed.ac.uk

Research Fellow

Research Fellows

Looking for researcher of exceptional talent to conduct 2 year research fellowship to work closely with Professor Philip Torr (http://cms.brookes.ac.uk/staff/PhilipTorr/), at Oxford Brookes vision research group http://cms.brookes.ac.uk/research/visiongroup to work on various projects connected with our ongoing work on scene understanding (see here for recent publications http://cms.brookes.ac.uk/staff/PhilipTorr/papers.htm).

There will be a large amount of freedom for the researcher and it is expected that applicants will have a top flight record, as evinced by publications in top venues such as ICCV, NIPS, ECCV, SIGGRAPH, CVPR, PAMI, JMLR, IJCV etc. The candidate will benefit from close mentoring to encourage them to develop into a top flight researcher.

The computer vision group at Oxford Brookes has a strong international reputation, having taken scientific best paper awards at all the conferences mentioned previously, it is an exceptionally stimulating environment, with strong connections to the top industrial research labs such as Sony, Microsoft and Google, as well as very close links with the Visual Geometry Group at Oxford University with whom we share reading groups and seminars.
It is soon to move to brand new facilities near the heart of Oxford, a very academically vibrant city.
The applications are competitive across disciplines, but those with a very good CV will take precedence.

For further information contact philiptorr@brookes.ac.uk or apply at http://www.brookes.ac.uk/services/hr/research_recruitment/index.html

The closing date for these vacancies is 11 January 2013.

CFP: Mathematics in Computer Science, Special Issue on Mathematics, Data and Knowledge

There is a growing interest in applying mathematical theories and methods (from topology, computational geometry, differential equations, fluid dynamics, quantum statistics, etc.) to describe and to analyze scientific regularities of diverse, massive, complex, nonlinear, and fast changing data accumulated continuously around the world and in discovering and revealing the valid, insightful, and valuable knowledge that data imply. With increasingly solid mathematical foundations, various methods and techniques have been studied and developed for data mining, modeling, and processing, and knowledge representation, organization, and verification; different systems and mechanisms have been designed to perform data-intensive tasks in many application fields for classification, predication, recommendation, ranking, filtering, etc. This special issue of Mathematics in Computer Science invites submissions of original research articles on the exploration of new mathematical theories and methodologies for data modeling and analysis, and knowledge discovery and management, on the study of existing mathematical models of big data and complex knowledge, and on the development of novel solutions and strategies to enhance the performance of existing systems and mechanisms for data and knowledge processing.

Specific topics include, but are not limited to:
• Mathematical foundations and theories for data-intensive and knowledge-based systems
• Mathematical, statistical, and dynamic analysis of data and knowledge models
• Mathematical methods for big data storage, transferring, and processing
• Mathematical methods for complex knowledge representation, organization, visualization, and management
• Mathematical methods for data mining, pattern recognition, artificial intelligence, and knowledge discovery
• Algebraic, geometric, analytic, discrete, probabilistic, fuzzy, rough set, and cognitive modeling of recommendation systems, ranking systems, rating systems, expert systems, etc.
• Mathematical theories for the development of evolutionary computing, neural networks, and genetic algorithms
Important Dates
• Deadline for paper submission: March 31, 2013
• Notification of acceptance: August 15, 2013
• Final paper submission: October 1, 2013
• Publication of special issue: December 2013

Submission Guidelines

Authors are encouraged to prepare submissions by using LaTeX with the class file mathincl.cls. Papers should be sent as PDF files to special.issue.mdk@gmail.com. All submitted papers will be refereed according to the usual MCS refereeing process. More information can be found at: http://mine.kaust.edu.sa/Pages/CFP-MCS-SI.aspx.

Guest Editors

Xiaoyu Chen, School of Computer Science and Engineering, Beihang University, China
Dongming Wang, Laboratoire d’Informatique de Paris 6, CNRS-UPMC, France
Xiangliang Zhang, King Abdullah University of Science and Technology, Saudi Arabia

Full Professor in Advanced Analytics

School of Business and Economics

We are seeking qualified applicants for teaching and research in the area of Advanced Analytics. The starting date is as soon as possible.

Within the “Excellence Initiative” – the German federal and state governments’ framework to promote cutting-edge research in and to enhance the quality of the country’s universities – the School of Business and Economics at RWTH Aachen University is currently in the process of establishing four Research Areas. All four of them will be brought together under one roof, that of the Interdisciplinary Management Factory (IMF), which will serve to substantially enhance the School’s research profile. Each Research Area will address global challenges, which can only be tackled via interdisciplinary and integrated research – a form of research that one of Europe’s leading universities of technology is optimally equipped to carry out.

The successful candidate will play a crucial role in establishing the Research Laboratory of the Operations Research and Management Research Area (ORM). The actors in this Research Area are economists, mathematicians, and computer scientists, whose research interests embrace operations research, operations management, discrete optimization, and efficient algorithms. The successful candidate will be expected to contribute to this pool of expertise with know-how from fields like prescriptive analytics, big data, or optimization under uncertainty/robust optimization. Apart from having conducted top-level research, reflected in publications in high-ranking journals, applicants should also demonstrate a successful professional orientation. Experience in procuring third-party funding is also very desirable. The teaching load will encompass two hours per semester. The professorship is limited to a period of four years.

A Ph.D. degree is required; additionally, Habilitation (post-doctoral lecturing qualification), an exemplary record of research achievement as an assistant / an associate / a junior professor or university researcher and/or an outstanding career outside academia are highly desirable. Ability in and commitment to teaching are essential. German is not necessary to begin. Applications from early-stage researchers are particularly welcome. Should more detailed information about this position be required, please contact Prof. Marco Lübbecke (luebbecke@or.rwth-aachen.de), who heads the ORM Research Area.

The application should include supporting documents regarding success in teaching.

Please send a cover letter stating research aims and a CV to: An den Dekan der Fakultät für Wirtschaftswissenschaften der RWTH Aachen, Prof. Dr. Oliver Lorz, D-52056 Aachen, Germany. The deadline for applications is December 12, 2012.

This position is also available as part-time employment per request.
RWTH Aachen University is certified as a family-friendly university and offers a dual career program for partner hiring. We particularly welcome and encourage applications from women, disabled people and ethnic minority groups, recognizing they are underrepresented across RWTH Aachen University. The principles of fair and open competition apply and appointments will be made on merit.

Postdoc: probabilistic ML and intensive care unit data

We are seeking a postdoctoral researcher at the University of Edinburgh to work on a project to develop and validate advanced statistical methods for analyzing time-series data from adult neuro-intensive care unit (NICU) patients.

The project would be suitable for candidates with a strong background in probabilistic machine learning who are keen to work on a challenging application area.

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.

In the first year the Research Associate will focus on methods for inferring physiological and artifactual events from time-series data, including data cleansing, anomaly detection, and inference in probabilistic models. This work will build on that of Quinn, Williams and McIntosh (PAMI, 2009) on Factorial Switching Linear Dynamical Systems applied to Physiological Condition Monitoring. In the second year of the project the models will be validated against live data collected at the NICU in the Southern General Hospital (Glasgow), and development of the models continued in light of the results obtained.

The postdoctoral researcher will be supervised by Prof Chris Williams , who may be contacted for informal enquiries.

For more information about the project and information about how to apply, please see http://homepages.inf.ed.ac.uk/ckiw/mypages/postdoc2013.html

or
https://www.vacancies.ed.ac.uk/pls/corehrrecruit/erq_jobspec_version_4.jobspec?p_id=007123

Please note the closing date of THURSDAY 10 JANUARY 2013, at 5pm UK time.

Chris Williams ckiw@inf.ed.ac.uk
Institute for Adaptive and Neural Computation School of Informatics, University of Edinburgh
10 Crichton Street, Edinburgh EH8 9AB, UK
tel: +44 131 651 1212 fax: +44 131 650 6899 http://homepages.inf.ed.ac.uk/ckiw/