Canadian AI, Graduate Student Symposium

22nd CANADIAN AI
http://ai2009.site.uottawa.ca

GRADUATE STUDENT SYMPOSIUM
http://www.site.uottawa.ca/~caropres/CAI09stsymp/cai09stsymp.html

CALL FOR PAPERS – Deadline January 30th, 2009

AI 2009, the twenty-second Canadian Conference on Artificial Intelligence, invites graduate students to submit four-page extended abstracts of their thesis for possible inclusion in the AI 2009 Graduate Student Symposium.

The Symposium provides an opportunity for Master’s and PhD students to discuss and explore their research interests and career objectives with their peers and with a panel of established researchers in Artificial Intelligence, helping to develop a supportive community of scholars and a spirit of collaborative research.

The symposium will be a one-day pre-conference event, where students of accepted abstracts will be invited to give a presentation on their thesis work before a group of peers as well as a small team of expert AI researchers who would offer a critique of each presentation and provide support, advice, and mentoring. Each student may also be invited to participate in the poster session during the main conference. In addition, a small selection of the best student submissions will be invited to give a short talk during the main conference.

PhD and Master’s students are invited to submit original work in all areas of Artificial Intelligence. It is not expected that submissions will consist of polished work with complete results; instead, more weight will be placed on the significance of the work, the proposed ideas or solutions, and the overall presentation. Submissions should therefore have emphasis on work in progress, with directions for future research clearly indicated wherever appropriate.

To apply for the symposium, please email an extended abstract in PDF, Postscript or MS-Word RTF to Svetlana dot Kiritchenko at nrc-cnrc dot gc dot ca, by January 30th, 2009. Each abstract has to be accompanied with a cover letter stating your name, institution, supervisor’s name and email address, program start date, expected graduation date, and 2-5 keywords describing your work. Also include a list of your refereed and non-refereed publications and presentations at national and international forums. All submissions must be written in English.

Abstracts may be up to 4 pages in length and must be formatted according to Springer's LNCS style. Please follow the instructions for authors at Springer's site for authors. The use of the LaTeX2e style file available at the web site is strongly encouraged. We anticipate all accepted abstracts to be included in the proceedings of the Canadian Conference on Artificial Intelligence 2009 published by Springer.

Each abstract will be reviewed by a mixed team of both students and program committee members. Presenting students will be selected based on clarity of the submission, stage of research, and evidence of promise such as published papers or technical reports. Partial financial assistance for travel and accommodations may be available to limited number of students presenting at the Symposium.

All students are encouraged to attend and participate in the Symposium, whether or not they apply to present their work. All the selected student presenters are expected to actively participate in the full Symposium, as we envision participants gaining as much by interacting with their peers as by having their presentations critiqued by the faculty panel. In addition, a senior AI researcher and faculty member will be invited to give a talk on a topic of interest to graduate students.

Important Dates

• Full paper submission due: January 30th, 2009
  
• Notification of acceptance: March 3rd, 2009
  
• Final paper due: March 12th, 2009
• Graduate Student Symposium: May 24th, 2009
  

Co-Chairs

• Svetlana Kiritchenko, National Research Council Canada
• Maria Fernanda Caropreso, University of Ottawa
  

Contact

• Svetlana Kiritchenko, National Research Council Canada
• Svetlana dot Kiritchenko at nrc-cnrc dot gc dot ca

Postgraduate Summer School on Computer Science and Information Systems 2009

Algarve, Portugal, 17 to 23 June 2009

(http://www.mccsis.org/school/)
parallel with IADIS Multi Conference on Computer Science and Information Systems (MCCSIS 2009) (http://www.mccsis.org)

Who can apply

The summer school is open to all participants enrolled in a PhD or doctoral course or in a master degree course, or recently having completed their postgraduate degrees in a higher education institution. There will be two classes, one with doctoral degree students and another with master
students.

Candidates for the summer school are expected to

• hold a master or baccalaureate degree in the areas of computer science or information systems for or an appropriate degree for the Summer Schools areas,
  
• have a previous knowledge in at least one area of the keynote lectures or the areas covered by the MCCSIS conference,
• demonstrate their ability to work in the field as researcher / student
  

The application process is governed by the rules determined and approved by the organizing committee of the summer school. The evaluation of the applications will be guaranteed by the organizing committee. The organizing committee will select the most promising candidates among the applicants.

Format of the Summer School

The Summer School will be held in conjunction with the Multi-conference on Computer Science and Information Systems (MCCSIS 2008). The registration fee from the Summer School will give access to

• Session on research methods;
• Session on the candidate's doctoral or master projects analysis and discussion;
• Keynotes from the conference keynote speakers in the selected areas ( 11 confirmed until now);
• Technical sessions from the MCCSIS conference;
• Tutorials from the conference (to be announced).

How to apply

Applications following the rules specified on the application form
should be sent through http://www.mccsis.org/school/

Important dates

Submission of Application - until 30 January 2009
Notification of acceptance - Until 6 March 2009
Registration - Until 6 April 2009
Late Registration: After 6 April 2009
Postgraduate Summer School - 17 to 23 June 2009

Secretariat

IADIS Secretariat - Postgraduate Summer School on Computer Science and Information Systems 2009 Rua Sao Sebastiao da Pedreira, 100, 3 1050-209 Lisbon, Portugal E-mail: sch...@mccsis.org Web site: http://www.mccsis.org/school/

Scientific Advisors

• Miguel Baptista Nunes, University of Sheffield, United Kingdom
• Piet Kommers, University of Twente, The Netherlands
• Nian-Shing Chen, National Sun Yat-sen University, Taiwan
• Pedro Isaías, Universidade Aberta (Portuguese Open University), Portugal

Job offer at FBK for Statistical Machine Translation, Trento - Italy

Call HLT09-01
Opening date: 12 January 2009 – Closing date: 31 March 2009

The “Human Language Technologies“ Research Unit of FBK (Trento, Italy) , is seeking a candidate to carry out research activities in the field of Statistical Machine Translation.

The candidate is expected to contribute original research results inside leading edge research projects, that aim to advance the state-of-the-art in MT by drawing ideas and contributions from different areas, such as machine learning, statistical language processing,high performance computing, statistical logic inference modelling, content processing from large corpora, etc.

More information about the HLT unit are available in http://hlt.fbk.eu

The ideal candidate should have:

• PhD Degree or post-graduate experience in MT or related fields
• Experience in statistical modelling and/or machine learning
• Skills in experimental work and development of algorithms in C++/C
• Ability to work in group and in distributed software development (open source)
• Ability to work and deliver in research projects
• Oral and written proficiency in English

Type of contract: 3 years, post-doc or research position. Possibility of tenure track.

To apply online please send your CV with relevant experience, qualifications and research interests to jobs@fbk.eu Ref. code: HLT09-01

UCL, Lecturership in Statistics

Lecturer in Statistics, UCL Department of Statistical Science

Applications are invited for a Lectureship available in the Department of Statistical Science, University College London from 1st September 2009.

Applicants should have research strengths in any branch of Probability and Statistics and an aptitude for teaching. They should also have, or expect to have in the near future, a PhD in Statistics or a related discipline. The successful applicant will be expected to carry out original research and to contribute to undergraduate and postgraduate teaching in Statistical Science.

An appointment will be made within the salary ranges £32,458 per annum
-
£35,469 per annum (Lecturer A) or £36,532 per annum - £43,622 per annum (Lecturer B), dependent upon skills and experience. London Allowance of £2,781 per annum will be paid in addition.

Further particulars, including the job description and person specification, can be viewed at http://www.ucl.ac.uk/Stats/department/jobs.html or may be obtained from Marion Ware, Departmental Administrator, telephone 020 7679 1872. Letters of application, including a CV and names of three referees, should be sent to:

Head of Department, Department of Statistical Science,
University College London, Gower Street, London WC1E 6BT. Tel: 02076791872,
Fax: 020 7383 4703, email: hod@stats.ucl.ac.uk.

UCL Taking Action for Equality.

The closing date for applications is Friday, 6th March 2009.

Vision and Sports Summer School

Zurich, 17-21 August 2009

http://www.vision.ee.ethz.ch/summerschool2009/

email: vs3@vision.ee.ethz.ch

application deadline: 10 May 2009


OVERVIEW

Vision and Sports is a special special kind of summer school. In addition to a broad-range of lectures on state-of-the-art Computer Vision techniques, it offers exciting sport activities, such as Kung-Fu, Ultimate Frisbee, and Volleyball. Sports will be organized by the same internationally renowned experts who deliver the lectures. The school offers the best of both worlds to participants: high-quality teaching on Computer Vision, and lots of fun with a variety of attractive sports. This will offer plenty of opportunity for personal contact between students and teachers.

The Vision and Sports Summer School will cover a broad range of subjects, reflecting the diversity of Computer Vision. Each lecture will cover both basic aspects and state-of-the-art research. Every day there will two Computer Vision classes and one sports session. The classes will include both lectures and practical exercises.

The school is open to about 40 participants, and is targeted mainly to young researchers (Master students and PhD students in particular).


CONFIRMED TEACHERS

Jiri Matas
Czech Technical University

Marc Pollefeys
ETH Zurich

Carsten Rother
Microsoft Cambridge

Bodo Rosenhahn
University of Hannover

Christoph Lampert
MPI Tuebingen

Bastian Leibe
TU Aachen

Vittorio Ferrari
ETH Zurich



COMPUTER VISION LECTURES

Topics will include:

• Local feature extraction
• Multi-view geometry
• 3D reconstruction
• Large-scale specific object recognition
• Appearance-based object categorization
• Shape representation and matching
• Contour-based object categorization
• Kernel Methods for Computer Vision
• Markov Random Fields and Conditional Random Fields for Computer Vision
• 3D human pose estimation

SPORT ACTIVITIES

Tennis, Volleyball, Ultimate Frisbee, Kung-Fu, Unihockey, Table Tennis


APPLICATION

The school is open to about 40 participants. Please apply online at

http://www.vision.ee.ethz.ch/summerschool2009/

Although priority will be given to young researchers (Master/PhD students in particular), applications from senior researchers and industrial professionals are welcome as well. The registration fee is expected to be around 300 Euro. This fee will include all classes, sports activities, coffee breaks, lunches, and a social dinner. For hotel accommodation, students will get discount rates on hotels affiliated with the Summer School.

Applicants should apply before 10 May 2009.
Notification of acceptance will be sent by 31 May 2009.


MORE INFORMATION

http://www.vision.ee.ethz.ch/summerschool2009/

PostDoc in Machine Learning in Human Computer Interaction

Our studies on computer supported collaboration rely on two eye tracking machines. These settings enable us to know, for instance, whether A is looking or not at the object that B is referring to verbally. Dual gaze patterns enable us to predict misunderstandings and even team performance. We aim to refine machine learning models to detect more elaborated patterns in dual eye tracking log files.

We are hence looking for a postdoc interested in applying machine learning to eye tracking data with the goal of inventing new collaboration technologies. Staring date to be negotiated.

Our lab (http://craft.epfl.ch) belongs to the School of Computer and Communication Sciences, at EPFL, the Swiss Federal Institute of Technology in Lausanne, Switzerland (http://www.epfl.ch). EPFL is ranked as one of the top universities in Europe. Lausanne, its lake
and its mountains, located at the center of Europe, offers a high quality of life.

Inquiries to pierre.dillenbourg@epfl.ch

Prof. Pierre Dillenbourg

Machine Learning Research Position - Hedge Fund

Based in Sydney, Australia, Boronia Capital Pty Ltd (formerly Grinham Managed Funds Pty Ltd) is one of the Southern Hemisphere's largest Hedge Fund Managers. Managing in excess of $1 billion we trade in over 60 futures markets into 9 countries, 24 hours a day. Boronia is committed to the development of statistically robust quantitative investment strategies through a disciplined scientific research process.

We are continuing to grow our research group and so are looking for individuals to fill a new permanent research position. The primary task will be to undertake research into the detection, modeling and exploitation of robust statistically significant patterns within financial time series data. The aim of this research is to develop new automated trading and execution strategies that complement those already in use.

The ideal applicant will have substantial research experience in machine learning, data mining or computational statistics, and a Ph.D. in one of engineering, physics, mathematics, statistics, computer science, finance or a related field. All levels of experience will be considered. Competency in software development is essential and a thorough knowledge of one or more of C, C++, Matlab/Octave or related languages will be required. Past experience with complex systems, large datasets, statistical and numerical analysis, or time series modeling will be highly regarded. Prior knowledge of or experience in finance is not a pre-requisite, though a strong interest in finance is essential. The working environment is informal, relaxed and has an academic feel. Hence researchers within the group have the possibility of publishing results from selected areas of their work, are encouraged to engage in collaborations with groups from outside the company, and are supported in conference attendance. The research group is divided into small teams (3-5), each with close IT support, so successful applicants should be willing to work harmoniously with other researchers and with the I.T. professionals that support the research.

This is an exciting, intellectually challenging and rewarding role for someone with enthusiasm, imagination and a desire to learn more about the dynamics of financial markets. Salary will be commensurate with experience. Bonuses are linked to seniority and performance.

Individuals who are interested may apply by emailing their resume to: Research2@boroniacapital.com.au

Vacancy PostDoc, Statistical NLP

The Institute for Logic, Language and Computation
http://www.illc.uva.nl

Postdoctoral Researcher

1.0 fte (38h per week)

For both internal and external candidates

Summary

• Position: POSTDOC researcher
• Duration: 2 years (full time, 38hrs per week)
  
• Salary (gross per month): minimum Euro 2379 and maximum Euro 3755 in the first year.
• The Collective Employment Agreement of the Dutch Universities is applicable.
• Last date for application: February 15, 2009.
  

Project

Priors for the Estimation of Probabilistic Grammars from Incomplete Natural Language Data
VIDI project Sima'an [2007-2011]

Abstract: The project aims at exploring the utility of available prior knowledge in specifying the model (hypothesis space) and the constraints on the objective estimation function for unsupervised estimation of probabilistic grammars for Statistical Machine Translation and Statistical Parsing.
This project addresses problems of unsupervised estimation in the face of different kinds of incomplete data (parallel and monolingual corpora):

1. A raw text corpus,
2. A partially annotated corpus possibly with negative examples, and
3. A raw in-domain corpus and an out-of-domain annotated corpus.
   

Corpus annotation is e.g., word-alignment, syntactic or semantic structure.

Example topics studied within the project (see project related publications):

• Statistical machine translation with hierarchical/syntactic structure, e.g., statistical estimation [Mylonakis and Sima'an 2007 and 2008], lexical syntactic structrure [Hassan, Way and Sima'an 2007 and 2008]
  
• Statistical machine translation with morphological structure -- Work in progress 2009,
  
• Inducing hidden compositional structure for machine translation (possibly using syntactic structure) -- Work in progress 2009.
  

Project team: Markos Mylonakis, Tejaswini Deoskar, and Khalil Sima'an (project leader).
Affiliated researchers: Reut Tsarfaty.
External collaborators: Hany Hassan , Barbara Plank and Andy Way.


Requirements

We seek a cooperative yet independent researcher who is passionate about empirical research, statistical methods and NLP/CL.
The following are the main requirements:

• obtained a Ph.D. recently (or will obtain it in the very near future, in which case testemoney from the PhD thesis Supervisor is needed)
• a strong background, experience in and affinity with the largest subset of the following areas:

1. Computational Linguistics/Natural Language Processing working with statistical methods
2. Machine Learning Applied to NLP with good knowledge of unsupervised statistical methods.
   
3. Statistical Machine Translation.
4. Unsupervised statistical methods for statistical Parsing.

Appointment

The appointment will be on a temporary basis for a maximum period of 2 years. Based on a full-time appointment (38 hours per week) the gross monthly salary will range from € 2379,- to, at the most, € 3755,- , in the first year depending on expertise and experience.

The Collective Employment Agreement of the Dutch Universities is applicable.

Application
To Dr Khalil Sima'an by email (k.simaan@uva.nl with subject heading: VIDI-POSTDOC).
The following documents (in pdf):

1. Letter expressing interest
   
2. Curriculum Vitae
3. List of publications (possibly including a downloadable pdf of your thesis)
   
4. Three letters of reference sent directly by the referees to Dr Khalil Sima'an
   
5. Optional: Research plan (1 page)

Last date for application: February 15, 2009.

For inquiries contact

Dr Khalil Sima'an.
Language and Computation
Computer Science
University of Amsterdam

Post-doc positions at the University of Southampton

Research Fellows (Two Posts) - Decentralised Control of Multi-Agent Systems

School of Electronics and Computer Science, University of Southampton, Southampton, UK.

Position Number: 2933-08-E
Closing Date: 22/12/2008
Location: Highfield Campus, Southampton
Salary: £27,183 - £33,432 per annum

http://www.jobs.soton.ac.uk/soton/jobboard/JobDetails.aspx?__ID=*6B21C139331FCAB9

Applications are invited for two Research Fellows in the Intelligence, Agents, Multimedia Group, in the School of Electronics and Computer Science at the University of Southampton. The School is the largest of its kind in the UK and was awarded the top grade of 5* for both Computer Science and Electronics in the last national assessment of research in UK universities.

The research positions will be associated with the Intelligent Decentralised Energy Systems (http://www.ecs.soton.ac.uk/research/projects/618) and the Aladdin (http://www.aladdinproject.org/) projects. These are both large, collaborative projects concerned with the decentralized control and operation of complex, dynamic systems. Specifically, the projects aim to study and apply multi-agent system techniques to the design, management, evolution and control of such systems. To do so, they draw on techniques from the realms of: game theory, distributed optimisation, decision theory, adaptive systems and mechanism design. Particular attention will be paid to the application of these techniques in the domains of disaster response, sensor networks and smart energy networks.

The posts will be based in the Intelligence, Agents, Multimedia research group (www.iam.ecs.soton.ac.uk) and will work with Professor Nick Jennings and Dr Alex Rogers. The successful candidate will join an internationally renowned team applying techniques from game theory, mechanism design, and multi-agent systems to a range of complex real-world problems.

You should possess a PhD in a relevant discipline (Computer Science, Engineering, Mathematics, Operations Research, or Economics) and have established a strong research pedigree in your area (as evidenced by publications in top quality journals and conferences). In particular, expertise in one or more of the following areas will be an advantage: multi-agent systems, game theory, decision theory, adaptive systems, and/or machine learning.

The Energy Systems post is for three years and the Aladdin post is for two years.

Informal enquiries may be made to Professor Nick Jennings (nrj@ecs.soton.ac.uk) or Dr Alex Rogers (acr@ecs.soton.ac.uk).

The closing date for applications is 15th January 2008 at 12.00 noon. Please quote reference number 2933-08-E on all correspondence.

Several fully funded PhD positions at Ghent University

Several fully funded Ph.D. positions in machine learning, speech recognition, handwriting recognition and robotics are available at the Reservoir Lab (http://reslab.elis.ugent.be) and the Speech Lab (http://speech.elis.ugent.be), both part of the Electronics and Information Systems Department, faculty of Engineering of the Ghent University, Belgium (http://ugent.be).

Project

Current state-of-the-art speech & handwriting recognition systems still perform much worse than human beings who can effortlessly decode the speech or handwriting of most people, even in fairly adverse conditions (e.g. the presence of noise in case of speech recognition). The fact that the human brain works so efficiently is owed to its self-organizing capacity, its deeply hierarchical approach, its adoption of unsupervised and supervised learning strategies, its capacity to adapt almost instantly to new circumstances, etc. Why not try to build an automatic speech recognizer and handwriting recognition engine that incorporates the same principles? This is exactly what we will do in two recently approved projects:

• “Self-organized Recurrent Neural Learning for Language Processing” (ORGANIC), funded by the European Commission within the 7th Framework Program. Details about the project can be found at the preliminary reservoir computing website (http://reservoir-computing.org).
• “Reservoir Computing for auditory pattern recognition” (RECAP), funded by the Research Program of the Research Foundation - Flanders (FWO).

The research concerns the investigation of architectures and algorithms for the efficient learning of large recurrent neural networks based on the Reservoir Computing concept (where only a linear readout layer is learned in a supervised way whereas the recurrent connections are fixed or trained in an unsupervised way). Important research topics are the unsupervised learning of a large hierarchy of recurrent sub-layers, and the integration of various adaptation techniques. The application domains are off-line handwriting recognition, speech recognition and various aspects of robotics (such as robot localization, motion control, ...). So far we were able to demonstrate that reservoirs can give rise to the robust recognition of digits spoken or written in isolation, but now we want to demonstrate that they can also yield robust recognition of continuous speech and handwriting (large vocabulary).

Requirements

Candidates should have a Masters degree in Electrical, Computer or Physics Engineering; or in Physics, Mathematics or Computer Science. A good knowledge of English is essential. No professional background is required, but the ideal candidates have some acquaintance with Machine Learning, programming (Python, Matlab, ...), statistics, signal processing, speech recognition, control engineering, or robotics.

What we offer

We offer an opportunity to perform at least three years of research in a new promising domain, and to get a doctoral degree in this domain. There will be ample opportunities for establishing international contacts (stays at partner universities, participation to international conferences). As an employee of the university you will receive a competitive salary (starting with a net monthly salary of approximately 1.600€) as well as excellent secondary benefits (holiday allowance, etc.). Belgium was ranked first on the “Best Countries for Academic Research” worldwide list (The Scientist, 2007), and Ghent University was appointed second place on the “Best Places to Work in Academia” non-US list (The Scientist, 2006).

Application and timing

If you are interested in one of the Ph.D. vacancies, please send in electronic format to Benjamin Schrauwen (Benjamin “dot” Schrauwen “at” UGent “dot” be): a detailed curriculum vitae, a motivation letter, your course program, your grades, two letters of recommendation and, if applicable, a publication list and selected publications. Do also mention your topics of preferences within the projects (e.g. robotics, speech, no preference, etc.). Some positions start on April 1, 2009, others in September 2009, meaning that persons who expect to graduate in July 2009 are welcome to apply. Applications which are received before February 1, 2009 get priority.

Post-doc in network models and machine learning in Paris, France

The Department Signal and Image Processing (TSI) of Telecom ParisTech (France) is offering a one year post-doctoral position in Machine-Learning. The post-doctoral fellow will develop and implement machine-learning procedures and statistical techniques for investigating the way information is spread through small social networks (<<>>). In the application considered, information is related to knowledge about dietary risks and the project include :

1. Model the information propagation phenomenon through the ego network according to several attributes describing the individuals and their relationships.
2. Design statistical procedures for quantifying the impact of network structure and descriptive variables on the propagation. Implementation will be based on the ALIMINFO data survey.
3. Extrapolate results to a larger scale through simulation and extra structural assumptions about the global network.

Required diplomas and skills : candidates will be recruited at the level of a PhD in Mathematics or Statistics. They will have confirmed skills in mathematical modelling, data analysis, statistical or machine learning methods, mathematical programming (Matlab or R), and will be highly motivated for applications to social sciences.

Funds: position is funded by a new Grant << Futur & Rupture << (Institut Telecom).

The Project Team: the candidate will enjoy a challenging and rewarding working environment,within a top leading laboratory in the field of Information and Communication Theory.

Members : Stephan Clemencon (Telecom ParisTech - TSI), Fabrice Rossi (Telecom ParisTech ?INFRES), Nicolas Vayatis (ENS Cachan - CMLA), Sandrine Blanchemanche (INRA Unite Met@risk), Akos Rona-Tas (UCSD Dept of Sociology).

Position starting March 2009, in Paris (France)

Net salary: ranging from 2200 to 2700 euros per month (depending on experience of the candidate)

Interested applicants should sent C.V. to :

Stephan Clemencon stephan.clemencon@telecom-paristech.fr

Telecom ParisTech - 37 rue Dareau - 75014 Paris ? France

Tel : +33 1 45 81 78 07, Fax : +33 1 45 81 71 58

Fully Funded PhD Studentship in Systems Biology

British Heart Foundation Fully Funded PhD Studentship in Systems Biology

MATHEMATICAL & STATISTICAL MODELLING OF CYTOKINE RECEPTOR CROSS-REGULATION BY CYCLIC AMP

Supervisors:

• Dr. Tim Palmer (t.palmer@bio.gla.ac.uk, Integrative and Systems Biology)
• Prof. Mark Girolami (girolami@dcs.gla.ac.uk, www.dcs.gla.ac.uk/inference)

Regulation of the immune/inflammatory responses by interleukin-6 (IL-6)-family cytokines is dictated by the interplay of multiple cytokine-activated signalling cascades and inhibitory regulators designed to prevent excessive receptor activation that can result in disease. The situation is further complicated by the observation that cytokine-activated signalling cascades are negatively controlled by distinct signalling modules such as those initiated by the prototypical intracellular messenger cyclic AMP. Despite its significance, the extensive level of cross-talk observed has not been integrated into coherent models of IL-6 receptor signalling and
its regulation.

Objectives

By combining molecular/cell biology with mathematical modelling & statistical inferential approaches, this inter-disciplinary studentship will A) statistically define minimal network structures that accurately describe cytokine signalling pathway kinetics, B) derive a set of plausible mathematical models that can identify the critical parameters controlling inhibitory cross-regulation of gp130 by cyclic AMP, and C) identify new approaches for limiting excessive cytokine signalling associated with inflammatory disorders.

The project provides an exciting opportunity for high-quality doctoral training in mathematical modelling & statistical inferential approaches and their application to increase our understanding of the architecture and dynamics of molecular cell signalling pathways. In addition to contemporary molecular and cellular biology techniques (mammalian cell culture, RNAi-mediated knockdown, protein analysis), the successful candidate will be trained in mathematical modelling of pathway dynamics as well as Bayesian statistical methods to formally characterize uncertainty in these models.

Candidates should be European Economic Area nationals, have an excellent first degree in a relevant mathematical discipline (Mathematics, Computing Science, Statistics, Engineering, Physics) and be highly motivated in their wish to apply this expertise to biological systems. Candidates with an excellent first degree in Biochemistry, Molecular and Cellular Biology or a related discipline, coupled with additional experience in applying mathematical/statistical methods to biological systems, will also be considered.

The studentship will commence as soon as possible after a suitable candidate is identified. The studentship will carry a stipend of £16,853 in year 1 and increasing to £18,580 in year 3. The studentship also covers the student’s university fees. The studentship is renewable, subject to satisfactory annual progress, for up to a total of three years.

Applications must consist of a current CV, contact details of at least two academic referees, evidence of degree performance, and a completed application form from http://www.gla.ac.uk/postgraduate/howtoapplyforaresearchdegree/

Preliminary email enquiries to Tim Palmer or Mark Girolami are welcomed.

Candidates are encouraged to complete the online application, but also to send their CV and associated documents direct to the Graduate School:

Graduate School of Biomedical and Life Sciences, Bower Building,
University of Glasgow, Glasgow G12 8QQ
Tel: ++44 (0)141-330-5800
Fax: ++44 (0)141-330-6093
E-mail: biograd@gla.ac.uk (please type “BHF Palmer” in the subject box of E-mails)
-------------------------------
Professor M.A. Girolami F.I.E.T
EPSRC Advanced Research Fellow
Department of Computing Science
Sir Alwyn Williams Building, Room 302
University of Glasgow
Glasgow, G12 8QQ
Scotland UK

Tel : +44 (0)141 330 1623
Fax: +44 (0)141 330 2673

email : girolami@dcs.gla.ac.uk
web: http://www.dcs.gla.ac.uk/~girolami
web: http://www.dcs.gla.ac.uk/inference

PhD Studenships at SUMO Lab, Belgium

3 PhD Student Positions at Ghent University

SUMO Lab (SUrrogate MOdeling Lab - http://www.sumo.intec.ugent.be) announces 3 openings for a PhD position in Machine Learning and Scientific Computing.

SUMO Lab is part of the IBCN research group (http://www.ibcn.intec.ugent.be) of the Department of Information Technology (INTEC) at Ghent University, Belgium.

We are looking for Masters degree candidates in engineering, computer science, physics or mathematics. Strong interdisciplinary interest in modeling and simulation, and supervised machine learning is required, and excellent programming skills (Matlab, Java) are highly desirable.

We offer fully paid 4 year PhD positions. The positions are funded by the Research Foundation Flanders. The positions are open to applicants of any nationality with good knowledge of English and/or Dutch.

The tentative starting date of the position is between now and October 2009.

We invite applicants to send their CV, as well as a short summary of their research interests by e-mail to Prof. Tom Dhaene (tom.dhaene@ugent.be).

PostDoc in ML, Discovery Systems Laboratory, Tennessee, USA

The Discovery Systems Laboratory has an open post-doctoral position in the area of machine learning and knowledge discovery. The lab's focus is on learning from data: (1) Development and
refinement of algorithms for knowledge discovery (including discovering cause and effect relationships) and (2) Application of knowledge discovery methods to various types of biomedical data including coded data, high throughput data, text and images.

Candidates with an earned PhD in computer science, information science, biomedical informatics or a closely related area with research interests in machine learning and knowledge discovery are encouraged to contact Subramani Mani by email (subramani.mani@ vanderbilt.edu).

For additional details about the DSL please visit www.dsl-lab.org

The DSL is part of the Department of Biomedical Informatics at Vanderbilt University located in Nashville, TN, USA.

PostDoc in ML / Mathematical Modeling of Neural Systems, Germany

A fully funded Postdoctoral Research Position in Machine Learning / Mathematical Modeling of Neural Systems is open in the research group of Herbert Jaeger (http://www.faculty.jacobs-university.de/hjaeger) at Jacobs University Bremen, Germany (http://www.jacobs-university.de).

The position is created in the context of the integrated project "Self-organized Recurrent Neural Learning for Language Processing (ORGANIC), funded by the European Commission within the 7th Framework Program "Cognitive Systems, Interaction, Robotics". Details about the project and the consortium can be found at the preliminary reservoir computing website (http://reservoir-computing.org). The project start is April 1, 2009 and the project duration is 3 years. The position may start earlier than the project start.

The projected research for this position concerns the architecture and learning algorithm design for large-scale recurrent neural network systems, with an emphasis on mathematical analysis. The targetted application area is speech and handwriting recognition. The project's overarching objective is to amalgamate neurobiological with engineering/mathematical perspectives, integrating a multitude of learning/adaptation/stabilization mechanisms for robustness and
versatility.

The ideal candidate would have the following qualifications:

• a PhD in machine learning, computational neuroscience, mathematics, theoretical physics, signal processing, control engineering, or similar fields,
• a strong mathematical background, especially in statistics and stochastic processes, nonlinear dynamics, and signals and systems,
• experience in machine learning, signal processing, nonlinear dynamics, recurrent neural networks,
• highly developed communication and organization skills,
• a very good command of English,
• endless curiosity.

Besides scientific work (80%), the task profile includes assistance in project management. This aspect of the position will extend the professional skills of the researcher in important directions of large-scale project coordination and leadership qualifications.

The total contract duration will be 3 years (project runtime, starting April 1) plus optionally the time from an earlier contract start to the project start. The application deadline is open.

Jacobs University Bremen is an equal opportunity employer and has been certified "Family Friendly" by the Hertie-Stiftung.

Please send in electronic format (PDF preferred) a letter of application, CV, a copy of academic certificates, and optionally samples of published work to Herbert Jaeger (h.jaeger@jacobs-university.de) who also invites further inquiries. Applicants passing an initial screening will be requested to supply two letters of reference.

PostDoc on Computer Vision and Machine Learning

Postdoctoral researcher in the field of computer vision and machine learning

The Learning Algorithm and Systems Laboratory at the EPFL (Swiss Federal Institute of Technology, Lausanne) seeks one qualified postdoctoral researcher in the field of computer vision and machine learning.

The postdoc will work in the framework of the IM2 and TACT projects, that develop algorithms for multimodal analysis of video and audio data recorded by the WearCam, a wearable hat designed for children with disabilities, see

http://lasa.epfl.ch/research/toys/wearcam/index.php

The successful candidate will have a PhD and experience in at least 1 of the following fields:

• computer vision or image processing
• machine learning, pattern recognition or statistical techniques

In addition, the candidate should have a strong background in C++ programming and matlab. The applicant should be fluent in English.

The initial Postdoctoral position is for one year, with a possibility of 1 year extension. The position is open immediately.

Application: Interested candidates should send a letter of motivation, along with their detailed CV, and copies of two relevant publications to Prof. Aude Billard (aude.billard@epfl.ch).

CMU, Portugal

Carnegie Mellon University and the Portuguese Government established a partnership, named as CMU-Portugal Program, with the objective of creating in Portugal first rate, internationally recognized, education and research programs in areas including, technology, critical infrastructures, risk assessment, innovation, and policy. Of special interest are machine learning methodologies that can be applied in the areas above.

IST is offering a Dual Carnegie Mellon University(CMU)/ Instituto Superior Tecnico (IST) PhD degree in Electrical and Computer Engineering. Upon completion, graduates will be awarded a degree both by CMU and IST. Students will be co-advised and will spend extended periods of time in both institutions.

Any Portuguese citizen or any foreign student admitted to IST is eligible for funding that covers tuition and a stipend. For further information, namely on how to apply see site list or contact the program coordinator :

IST
http://cmuportugal-ece.ist.utl.pt/
http://www.ist.utl.pt/en/html/cmu-pt/

Carnegie Mellon University
http://www.icti.cmu.edu
http://www.ece.cmu.edu/prospective/graduate/admissions.html

Joao Costeira
Coordinator PhD Dual Degree in ECE
Instituto Superior Tecnico-
Av. Rovisco Pais
1049-001 Lisboa, Portugal
Email: cmuportugal-ece@isr.ist.utl.pt

PhD and PostDoc position in ML at AI Labratory, University of Geneva, Switzerland

Applications are invited for one PhD and one post-doctoral position in the Artificial Intelligence Laboratory (Computer Science Department) of the University of Geneva. The successful candidates will participate in European and national research projects, where they will combine theoretical, experimental and applied research in machine learning and data mining. Further information on the research activities of the AI Lab can be found on http://cui.unige.ch/AI-group.

Candidates should have a solid background in both computer science and mathematics, particularly in statistical learning and optimization theory. They should have excellent programming skills as well as communication skills in English (and ideally in French). Preference will be given to candidates with a strong interest and/or experience in advanced knowledge discovery issues such as multisource learning, integration of prior knowledge into the data mining process, or generalization from high-dimensional small samples. Training or experience in one or several application areas (e.g., physics, biology, social sciences) will be appreciated. A strong academic record, excellent analytical skills and a clear aptitude for autonomous, creative research will be priority selection criteria.

Applications should include a CV, academic transcript, a brief statement of purpose, a list of publications, and names and e-mail addresses of at least 2 references.

Funding will start on 1/10/2008 and 1/2/2009 for the PhD and postdoc positions respectively. Starting salary will be around 4100 CHF at the PhD and 5380 CHF at the postdoc level (1 CHF = 0.646 EUR). Applications will be accepted until both positions are filled.

Please send your applications (preferably by e-mail) to

Melanie.Hilario[at]unige.ch
CUI - University of Geneva
Battelle A, 7 route de Drize
CH-1227 Carouge, Switzerland

Research Fellow, Statistics/Machine Learning at University of Edinburgh

Research Fellow (Statistician, Machine Learning Specialist)
£29,704 - £35,469

A research post is available immediately at the University of Edinburgh for a Bayesian statistician/computer scientist to work on developing statistical methods for genetic epidemiology. The object is to develop methods for modelling the joint effects of genotype and environment and inferring causal relationships, using tools such as Markov chain Monte Carlo simulation, variational Bayes approximations, and Dirichlet process models. The successful applicant is likely to learn about and make use of the recently released Infer.NET (http://research.microsoft.com/infernet), as well as developing other techniques.

The post would suit an individual at post-doctoral level with experience of using and developing Bayesian probabilistic methods for modelling and inference. Previous experience in statistical genetics or bioinformatics is useful, but is far from an essential requirement: experience in novel
development and application of probabilistic machine learning and statistical methods in other fields could be just as valuable. The post is funded by the Medical Research Council for three years with possibility of extension should further funding be obtained.

Closing date: 9 January 2009.

See http://www.jobs.ac.uk/jobs/RO886 /Research_Fellow_Statistician_Machine_Learning_Specialist/

Interested applicants can contact Paul McKeigue (paul.mckeigue@ed.ac.uk) or Amos Storkey (a.storkey@ed.ac.uk) for further details.