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.