PhD opportunities in bioinformatics and biomathematics

Bristol Centre for Systems Biomedicine
Doctoral Training Programme in Bioinformatics and Biomathematics

Bristol Centre for Systems Biomedicine represents an innovative interdisciplinary doctoral training programme offering fully funded 4 (1+3) year studentships, five available in October 2009, five available in 2010. Under the Medical Research Council Capacity Building scheme, these studentships have a £2K pa top up added to the standard stipend of £13K pa, plus tuition fees
and travel/meetings allowance.

High calibre graduates from mathematical, engineering and computationally related disciplines
with a strong interest in developing these skills and applying their abilities to biomedical research, will be trained in a structured and broad programme of relevant short courses, seminars, short (3x3month) projects, and a full PhD project. Programme topics range from population dynamics to the different ‘omics’ (e.g. genomics, proteomics) and pathway and molecular applications. It includes mathematical, statistical and genetic epidemiology, evolutionary, behaviour and mutation theory, evidence synthesis, decision sciences and trials, cell signalling, omics technologies
network inference, DNA, RNA and protein prediction and mathematical modelling in neurophysiological contexts.

In the first core foundation year, students will have a group base in Oakfield House
http://www.bristol.ac.uk/university/maps/google-precinct/index.html.
The programme is led from the Department of Social Medicine with close co-supervisory arrangements with the Departments of Mathematics, Engineering Mathematics, Computer Science and other groups from the medical faculties at the University of Bristol. The host departments all gained very high ratings in RAE2008. BCSBmed is also closely interlinked with five other MRC, Wellcome Trust and EPSRC doctoral training centres in Bristol.

For information about the university, please visit http://www.bristol.ac.uk/ and for a further details: http://www.findaphd.com/

For application forms, please contact the Programme Director, Prof. Ian Day, ian.day (at) bristol.ac.uk.
Please mark your subject line ‘BCSBmed application forms request’ : you will receive an automatic reply.

For information pack or informal enquiries, please contact ian.day (at) bristol.ac.uk, subject line marked ‘BCSBmed information request’.

Further informal enquiries can be directed to C.Campbell (at) bris.ac.uk, subject line marked ‘BCSBmed enquiry’

Open Position : Postdoc in Computational Biology, Cambridge, UK

The genetics lab of Prof. Sir Bruce Ponder and the computational biology lab of Dr. Florian Markowetz at the Cancer Research UK Cambridge Research Institute offer a joint position for a postdoctoral researcher interested in statistical and computational approaches to systems genetics in cancer.

The recent whole-genome scan for breast cancer [1] has identified five novel susceptibility loci. In follow-up work the strongest locus has been narrowed down to two SNPs in the intronic region of the FGFR2 gene [2]. However, a detailed understanding of the disease mechanism is still missing. This project will use a systems biology approach to elucidate the functional roles of FGFR2 and other cancer susceptibility genes. We will integrate diverse genomic data sources (including gene expression, SNPs, copy number variants and others) using statistical network methods [3]. The resulting networks will be used to identify key drivers of disease and their functional mechanisms. The methods developed in breast cancer will also be applied to other cancer types, e.g. lung cancer.

The position bridges between an experimental and a computational lab and is ideal if you are interested in data analysis and method development motivated by close collaborations with experimentalists.

The ideal applicant has a strong background in data analysis and statistical modelling (including knowledge of R or Matlab). Experience in medical or biological research is desireable.

If you are highly motivated to work in an interdisciplinary and very collaborative environment at an internationally recognized research institute, apply by sending your CV to Florian Markowetz at
florian.markowetz (at) cancer.org.uk.

For more information please visit http://www.markowetzlab.org

References

1. DF Easton, …, BAJ Ponder Nature 2007. PMID 17529967
2. KB Meyer, … , BAJ Ponder PLoS Biology 2008. PMID 18462018
3. F Markowetz and R Spang, BMC Bioinf, 2007. PMID 17903286

PhD thesis grant: machine learning and multimodal data

The research labs LIF (http://www.lif.univ-mrs.fr) and LSIS (http://www.lsis.org) together propose a PhD thesis in machine learning applied to multimedia data, within the « Web Multimedia Mining » research group. The thesis will take place in Marseille and Toulon, south-east of France (french riviera), starting in fall 2009. It is granted by the French Minister of Education and Research for 3 years.

The thesis aims at theoretically studying co-training style algorithms to fit multimodal concerns, with application to scaled benchmarks of multimedia data, and the participation to the TRECVID international challenge. The description of the thesis can be found at
http://www.lif.univ-mrs.fr/spip.php?article423.

Supervisors: François Denis, PR (LIF), francois.denis (at) lif.univ-mrs.fr and Hervé Glotin, MCF HDR (LSIS), glotin (at) univ-tln.fr.

Conditions for application: candidates must hold a Master Degree in computer science.

Required skills: fundamental computer science, statistics, machine learning, signal processing, multimedia data representation. Algorithmics and programmation. The candidate must have a master degree in computer science. Matlab and C programming are welcome.

How to apply: please contact the supervisors and send them a Curriculum Vitae with recommandations if any. Deadline for application: july 9th, 2009.

Announcement: Workshop on Structure Adapting Methods, Berlin 6-8 November 2009

Workshop on Structure Adapting Methods
Berlin, 6-8 November 2009
http://www.wias-berlin.de/workshops/sam09/

Registration deadline: October 22, 2009

Scope:

One possible way out of the curse of dimensionality problem is based on one or another structural assumption which allows to reduce the complexity/dimensionality of the model. A number of such structural assumptions is popular in the statistical literature including single- and multiple-index, additive, models, projection pursuit and sparse models, among many others. Knowing the structure allows for applying the classical methods to the reduced models. Unfortunately, the exact structural information is rarely available and the related problem is to extract the structural information from the data as an important preprocessing step.

The aim of this workshop is bringing together leading specialists from the field of adaptive estimation for discussing the new approaches, ideas, challenges and addressing the algorithmic and mathematical aspects of this new and actively developing area of mathematical statistics and machine learning.

Preliminary list of invited speakers:

Peter Bühlmann
Alexander Goldenshluger
Yuri Golubev
Wolfgang Härdle
Joel Horowitz
Anatoly Juditsky
Gerard Kerkyacharian
Oleg Lepski
Mikhail Malioutov
Grigory Milstein
Dominique Picard
Ya’acov Ritov
Alexander Tsybakov

2 Lecturerships in Sheffield, UK

Job Title: Lecturer in Automatic Control & Systems Engineering (2 Posts)
Department: Department of Automatic Control & Systems Engineering

Ref No: R07355

Closing Date: 31st August, 2009

Salary: £36,532 – £43,622 per annum with the potential to progress to £49,096

Summary

Outstanding individuals are sought for two lectureship positions to complement and enhance the multi-disciplinary research portfolio of the Department of Automatic Control and Systems Engineering. Research experience and expertise in (i) Robotics (ii) Aerospace and Transport Systems or (iii) Systems Modelling and Optimisation in Healthcare or in Manufacturing is preferred. Applicants with a strong general background in Systems, Signal Processing and Control are also encouraged to apply. If successful, you will be expected to work closely with relevant department and faculty based research centres. You must have a good first degree and a PhD (or equivalent experience) in a related subject. In addition, you should display an ability and willingness to teach
across the range of taught programmes and to work as part of a team.

http://www.sheffield.ac.uk/jobs/academic.html

Open PhD/Post-doc positions ErcStG MiGraNT project

The MiGraNT project (ERC Starting Grant 240186 : Mining Graphs and Networks: a Theory-based approach) has several (3 to 5) open positions for PhD students and post-doctoral researchers.

The MiGraNT project aims at developing a sound theoretical understanding of mining and learning with graphs, and to exploit this theory to construct effective algorithms for significant real-life applications. Key features of the methodology include the integration of insights from graph theory in data mining and learning approaches, the development of efficient prototype algorithms, and the interdisciplinary collaboration with application domain experts to validate the practical value of the work,

Candidates should have a master in computer science, statistics or mathematics, a PhD in data mining, statistics, graph theory, algorithmics or theoretical computer science, or equivalent. Successful candidates can start on 01/12/2009 or later (negotiable), and funding is possible for up to 5 years.

The host institution of the MiGraNT project is the K.U.Leuven, Belgium, The K.U.Leuven has a strong history of machine learning and data mining research, and offers plenty of opportunities for interactions with researchers of application domains such as medicine, biology, chemistry and computer networks.

Candidates are requested to express their interest by sending email to Jan Ramon (see below) before September 15th, including CV, publication list and names of references.

* Location: Machine learning group (http://www.cs.kuleuven.be/~dtai/ml/), Department of computer science, K.U.Leuven (http://www.kuleuven.be), Leuven, Belgium
* Contact person: Jan Ramon (http://www.cs.kuleuven.be/~janr/ ; Jan (dot) Ramon (at) cs (dot) kuleuven (dot) be)
* More information: http://www.cs.kuleuven.be/~janr/MiGraNT/

SSPR+SPR 2010 Conferences: Call for Participation

Joint IAPR International Workshops on Structural and Syntactic Pattern Recognition (SSPR 2010) and Statistical Techniques in Pattern Recognition (SPR 2010)

18-20 August 2010, Cesme, Izmir, Turkey.

The next joint Statistical Pattern Recognition and Structural and Syntactic Pattern Recognition Workshops (organised by TC1 and TC2 of the International Association for Pattern Recognition, IAPR) will be held in Cesme, Turkey prior to ICPR 2010 (which itself will be held in Istanbul). The joint workshops aim at promoting interaction and collaboration among researchers working in areas covered by TC1 and TC2. We are also keen to attract participants working in fields that make use of statistical, structural or syntactic pattern recognition techniques (e.g. image processing, computer vision, bioinformatics, chemo-informatics, machine learning, document analysis, etc.). Those working in areas which can make methodological contributions to the field, e.g. methematicians, statisticians, physicists etc, are also very welcome.

The workshop will be held in Cesme, which is a seaside resort on the Aegean coast of Turkey. There area has many interesting attractions including excellent beaches, interesting fishing villages, and nearby archaeological remains and historical sites. These include Cesme castle and the remains of the ancient Greek city of Erythrae. Cesme can be reached by bus from the airport at Izmir, which has good flight connections to Istanbul.

We hope to have a varied programme including invited talks, regular paper and poster sessions, panel sessions and technical committee meetings.

Organisation:

General Chair: Edwin Hancock (University of York)
General co-chair: Ilkay Ulusoy (Middle East Technical University, Ankara)
SPR Programme Chair: Terry Windeatt (University of Surrey)
SSPR Programme Chair: Richard Wilson (University of York)
Publicity Chair: Francesco Escolano (University of Alicante)

Programme Committee: to be confirmed.

Confirmed Invited Speakers:

Narendra Ahuja (UIUC), Chris Bishop (Microsoft Research)

Provisional Dates:

Submission of papers: 1st February 2010
Decisions: 1st April 2010
Camera ready copy: 1st May 2010
Workshops: 18-20 August 2010.

Scope:

Papers may address any topic in statistical, structural or syntactic pattern recognition. Possible topics of interest include, but are not limited to:

SSPR Topics

Structural Matching
Syntactic Pattern Recognition
Image Understanding
Shape Analysis
Graphical Models
Graph-Based Models
Spectral Methods for Graph Based Representations
Probabilistic and Stochasitc Structural Models for Pattern Recognition
Structural Learning in Spatial or Spatio-Temporal Signals
Kernel Methods for Structured Data
Image and Video Analysis
Intelligent Sensing Systems
Spatio-Temporal Pattern Recognition
SSPR Methods in Computer Vision
Multimedia Signal Analysis
Image Document Analysis
Structured Text Analysis and Understanding
Novel Applications

SPR Topics :

Density Estimation
Large Margin Classifiers
Kernel Methods
Ensemble Methods and Multiple Classifiers
Bayesian Methods
Gaussian Processes
Dimensionality Reduction
Independent Component Analysis
Cluster Analysis
Unsupervised Learning
Data Visualization
Semi-Supervised Learning
Model Selection
Hybrid methods
Comparative Studies
Speech and Image Analysis
Novel Applications

Call for participation: ECML-PKDD ws on Learning from Non-IID Data

Call for Participation
Workshop on Learning from non-IID data: Theory, Algorithms and Practice
During ECML-PKDD 2009
7 September 2009, Bled, Slovenia

Description
———–
Both classification and regression frameworks in Machine Learning were developed under the independently and identically distributed (IID) assumption. Though this assumption helps to study the properties of learning procedures (e.g. generalization ability), and also guides the building of new algorithms, there are many real world situations where it does not hold. This is particularly the case for many challenging tasks of machine learning that have recently received much attention such as (but not limited to): ranking, active learning, hypothesis testing, learning with graphical models, prediction on graphs, mining (social) networks, multimedia or language processing.

This workshop is the first one that adresses specifically the problem of learning from non-IID data. The goal of the workshop is to bring together research works aiming at identifying problems where either the assumption of identical distribution or independency, or both, is violated, and where it is anticipated that carefully taking into account the non-IIDness is of primary importance.
Examples of such problems are:

– Bipartite ranking or, more generally, pairwise classification, where pairing up IID variables entails non-IIDness: if the data may still be identically distributed, they are no longer independent;

– Active learning, where labels for specific data are requested by the learner: the independence assumption is also violated;

– Learning with covariate shift, where the training and test marginal distributions of the data differ: the identically distributed assumption does not hold.

– Online learning from streaming data, when the distribution of the incoming examples changes over time: the examples are not identically distributed.

Keynote Speakers
—————-
Shai Ben-David, University of Waterloo, Canada
Title: Towards theoretical understanding of domain adaptation learning

Nicolas Vayatis, École Normale Supérieure de Cachan, France
Title: Empirical risk minimization with statistics of higher order with examples from bipartite ranking

Workshop Program
—————-
More information on the workshop website
http://www-connex.lip6.fr/~amini/ecml-wk-lniid.html

Program Committee
—————–
Shai Ben-David, University of Waterloo, Canada
Gilles Blanchard, Fraunhofer FIRST (IDA), Germany
Stéphan Clémençon, Télécom ParisTech, France
François Denis, University of Provence, France
Claudio Gentile, University dell’Insubria, Italy
Balaji Krishnapuram, Siemens Medical Solutions, USA
François Laviolette, Université Laval, Canada
Xuejun Liao, Duke University, USA
Richard Nock, University Antilles-Guyane, France
Daniil Ryabko, INRIA, France
Marc Sebban, University of Saint-Etienne, France
Ingo Steinwart, Los Alamos National Labs, USA
Masashi Sugiyama, Tokyo Institute of Technology, Japan
Nicolas Vayatis, École Normale Supérieure de Cachan, France
Zhi-Hua Zhou, Nanjing University, China

Organizers
———-
Massih-Reza Amini, National Research Council, Canada
Amaury Habrard, University of Marseille, France
Liva Ralaivola, University of Marseille, France
Nicolas Usunier, University Pierre et Marie Curie, France

Sponsors
——–
-Laboratoire d’Informatique Fondamentale de Marseille (LIF)
http://www.lif.univ-mrs.fr
-PASCAL2 Network of Excellence
http://www.pascal-network.org
-ECML-PKDD 2009 organisation
http://www.ecmlpkdd2009.net

Contribution to PASCAL industrial outreach meeting

We solicit contributions from PASCAL researchers to showcase their (PASCAL sponsored) research within an industrial and business setting.

The SMART-PASCAL industrial outreach meeting will take place on the 7th of September prior to ECML in Bled, Slovenia

http://pascallin2.ecs.soton.ac.uk/Outreach/

Please email potential contributions to nello.cristianini (at) gmail.com

Few Places Still Available: The Analysis of Patterns 2009

You are invited to participate in the third course on:

THE ANALYSIS OF PATTERNS
Pula Science Park (Cagliari)
Pula, Italy
September 27th – October 3rd, 2009
http://www.analysis-of-patterns.net/

Organizers: Nello Cristianini, Fabio Roli, Tijl de Bie

LECTURERS:
* Florent Nicart – Université de Rouen

* Jean Philippe Vert – Mines Paris Tech

* John Shawe-Taylor – University College London

* Nello Cristianini – University of Bristol

* Bart Goethals – University of Antwerp

* Elisa Ricci, Idiap

* Fabio Roli, University of Cagliari

+ Research Seminars (to be announced)

DESCRIPTION

Every aspect of modern society has been affected by the data revolution. Cheap collection, storage and transmission of vast amounts of information have revolutionized the practice of science, technology and business.Ideas from various disciplines have been deployed to help in the task of designing computer systems that can automatically detect and exploit useful regularities (patterns) in general types of data.

This is the third meeting of a series devoted to pursuing a unified theoretical description of the various branches of Pattern Analysis. These include statistical approaches to pattern recognition, combinatorial approaches to pattern matching, grammatical representations of structures, and many more fields of mathematics and computer science. The summer school will aim to emphasize a
fundamental unity in goals and methods in all these diverse fields, to enhance our understanding of the central principles of pattern analysis, and to assist in the development of new pattern analysis approaches.
The meeting is interdisciplinary in nature, and can be seen both as a School for advanced students, and as a Workshop for researchers. Leading researchers in various subfields of pattern analysis will hold tutorials on their subject area, while new ideas will be presented in poster sessions, discussions and short seminars. Students in machine learning, pattern recognition, statistics, optimization, data mining, bioinformatics, are particularly encouraged to apply.

REGISTRATION:
The registration fee for the School is 680 Euro per person for a double room (820 Euro for a single room) and includes 7 nights accommodation, meals and school fees.

Attendance is limited to 50 students and will be allocated on a first-come-first-served basis.

http://www.analysis-of-patterns.net/

Closing date: June 1st, 2009