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.

CALL FOR PAPERS

CAIP 2013

15th International Conference on
Computer Analysis of Images and Patterns

27-29 August 2013

York, United Kingdom

http://http://www.cs.york.ac.uk/cvpr/caip2013/

CAIP 2013 is the fiftheenth in the CAIP series of biennial
international conferences devoted to all aspects of Computer
Vision, Image Analysis and Processing, Pattern recognition
and related fields. CAIP2013 will be hosted by York University

This is a call for contributions for the following 3-day workshop:
*Industry & Practices for Forecasting -- second edition* to be held 3 miles away from Paris, from June 5 to 7, 2013.

Its focus is on the forecasting of time series using stochastic modeling and/or learning methods, in a high dimensional context.

The purpose is to bring together academics and industry professionals to share different experiences and discuss future trends related to this area.
Both theoretical and practical issues will be considered.

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Apologies for cross-posting.
It would be appreciated if you could forward this to any interested parties.
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Applications are invited for four fully-funded 4-year PhD positions and one fully-funded 3-year post-doc position in the area of Statistical Machine Translation. The positions are funded through an advanced research fellowship (Vidi scheme) by the Dutch Science Foundation (NWO) and a governmental research grant.

Please find further details (including the application procedure) for the PhD positions at:

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.

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
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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.

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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.

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

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.

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.