Showing posts with label machine learning. Show all posts
Showing posts with label machine learning. Show all posts

PostDoc in Machine Learning in Human Computer Interaction

. Thursday, January 15, 2009
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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

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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

Several fully funded PhD positions at Ghent University

. Thursday, January 8, 2009
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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

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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

PhD Studenships at SUMO Lab, Belgium

. Monday, January 5, 2009
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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

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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

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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

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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

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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

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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

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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.

PostDoc in Signal and Image Processing, Paris

. Thursday, December 25, 2008
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POST-DOCTORAL POSITION - 2009 Department : Signal and Image Processing http://www.tsi.enst.fr/

Lab : LTCI UMR Telecom ParisTech/CNRS 5141 http://www.ltci.enst.fr/

TOPICS : machine-learning for structured data, social networks, random graphs, graphical models

Description : 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 (« ego networks »). The main focus of this research project lies on information related to knowledge about dietary risks.

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 : Stéphan Clémençon (Telecom ParisTech - TSI), Fabrice Rossi (Telecom ParisTech – INFRES), Nicolas Vayatis (ENS Cachan - CMLA), Sandrine Blanchemanche (INRA Unité 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 :
Stéphan Clémençon 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

Summer Schools in Logic and Learning

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An Open Invitation to attend the Summer Schools in Logic and Learning 26 January to 6 February 2009 Australian National University, Canberra, Australia

One of the grand challenges in science and engineering is to build computer systems that are trustworthy and intelligent. While achieving this goal could be many decades away, computer systems are clearly getting smarter and more reliable year by year and human society is becoming more reliant on exploiting their increasing intelligence. Logic and machine learning are two indispensable parts of the efforts to meet this challenge.

Join us for a new summer school experience where you have a unique two week opportunity to combine the solid foundations of logic and machine learning, with an introductory track in artificial intelligence in the second week.

Courses are taught by some of the world's leading computer scientists and blend practical and theoretical short courses with lectures and demonstrations in state-of-the-art computer facilities at ANU.

Courses and Speakers

Artificial Intelligence Courses http://ssll.cecs.anu.edu.au/speakers/ai

Logic Courses http://ssll.cecs.anu.edu.au/speakers/lss

Machine Learning Courses http://ssll.cecs.anu.edu.au/speakers/mlss

Fees and Registration http://ssll.cecs.anu.edu.au/registration

More information http://ssll.cecs.anu.edu.au/

If you would like to discuss this invitation in more detail, including advice on suitable candidacy, please go to http://ssll.cecs.anu.edu.au/about/contact

The Summer Schools in Logic and Learning are supported by ANU and NICTA.

Committee

Dr Tiberio Caetano, Convener
Professor John Slaney, Convener
Dr Alwen Tiu (Acting Convener)
Diane Kossatz
Michelle Moravec

Open positions in Machine Learning, Lille (France)

. Sunday, December 7, 2008
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We would like to advertise that tenure positions for researchers will be opened soon by the French National Research Institute for Computer Science and Control (INRIA, http://www.inria.fr/index.en.html).

In Lille, two research groups have strong interest in machine learning:
We would also like to mention that opportunities exist for:
  • tenure positions for senior researchers in order to create a new research group
  • five years positions for senior researchers
  • postdoctoral positions
  • PhD grants
A thorough description of these opportunities is given on our Web sites.

If you have any question, please get in touch with us, either remi.gilleron@inria.fr (Mostrare), or remi.munos@inria.fr, philippe.preux@inria.fr for SequeL. If you want to apply, it is crucial that you get in touch with us, as early as possible.

Post doctoral position in Machine Learning/Cognitive Vision/CBIR

. Friday, December 5, 2008
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For a project funded by the Austrian Science Foundation (FWF) and the European Commission, we are looking for a highly motivated post doctoral researcher with background in machine learning and/or cognitive vision and/or content based image retrieval. Among the possible fields of specialization are on-line learning, active learning, reinforcement learning, visual object classification, relevance feedback, and query-by-example search.

To learn more about the above project and the research at the Chair of Information Technology, University of Leoben, Austria, please visit http://institute.unileoben.ac.at/infotech.

This position will be filled in January 2009 for the duration of 2 years (with a possible extension). Depending on your qualification salary is 30000-45000 EUR per year (after paying all social and insurance benefits and taxes this is net 1500-2000 EUR per month). Highly qualified PhD candidates may be considered as well.

Applicants should submit 1) a CV, including a brief research statement, 2) 1-3 recent publications in electronic format, and 3) the names and contact information of three individuals who can serve as references.


Contact:

Univ.-Prof. Dr. Peter Auer
University of Leoben
Chair for Information Technology
Franz-Josef-Strasse 18, A-8700 Leoben, Austria
Fax: +43(3842)402-1502
E-mail: auer@unileoben.ac.at

PostDoc job in Planning under Uncertainty

. Monday, January 21, 2008
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PostDoc job in Planning under Uncertainty

A postdoctoral research grant is available at the Institute for Systems and Robotics (ISR) of the Instituto Superior Técnico, Lisbon. The topic of the grant is planning under uncertainty in the context of multi-robot search and rescue. The goal is to develop methodology and algorithms for heterogeneous teams of robots involved in urban search-and-rescue tasks. Planning in such scenarios requires agents to handle uncertainty in acting, sensing as well as communication.
Decentralized partially observable Markov decision processes form a state-of-the-art formal approach for multiagent planning, and we intend to apply them to multi-robot search-and-rescue tasks. More details can be found at http://www.isr.ist.utl.pt/~mtjspaan/decpucs/ .

ISR-Lisbon is a research institute of the Instituto Superior Técnico, the oldest and largest engineering school in Portugal. ISR-Lisbon has a long standing tradition of research and development and offers a modern and enthusiastic research environment with strong interdisciplinary and international links.

The grant has duration of (a maximum of) two years, and candidates should have obtained a relevant PhD degree (e.g., Computer Science, Artificial Intelligence, Electrical Engineering). The ideal candidate has expertise in Markov decision processes and multiagent/multi-robot systems. Applications should include CV, a statement of research interests and two recommendation letters, and be sent to Dr. Matthijs Spaan at mtjspaan@isr.ist.utl.pt or fax: +351-21-8418291, who can also be contacted for more information. Application deadline is February 7, 2008.

Postdoc: Handwriting recognition Scientist

. Friday, January 4, 2008
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A2iA (Artificial Intelligence & Image Analysis) is the worldwide leading developer of natural handwriting recognition, Intelligent Word Recognition (IWR) and Intelligent Character Recognition (ICR) technologies and products for the payment, mail, document and forms processing markets.

We are looking for a Handwriting recognition Scientist for our R&D Department in Paris.

This position requires a person with a strong background in machine learning methodology, algorithms for recognition (speech, handwriting), and software development. The primary responsibilities are to conduct research and software development for handwriting recognition using statistical machine learning methods.


ESSENTIAL DUTIES:
  • Develop new algorithms for handwriting recognition based on statistical machine learning techniques.
  • Responsible for the development and implementation of core computational routines in C++ and python interface, automated test and validation routines, and related documentation such as help files and user's guide.
  • Develop tests to verify the algorithms and the robustness of the methodologies and software in the areas of handwriting recognition in a wide variety of real world applications.
  • Author technical papers related to algorithms, methodology, and case study results.
  • Interest and willingness to conduct novel research in handwriting recognition and machine learning.

ESSENTIAL KNOWLEDGE AND SKILLS:

Education and Training: Ph.D. in Computer Science, Statistics, Applied Mathematics, or related
field.

SPECIALIZED KNOWLEDGE AND SKILLS:
  • Strong background data mining and statistical machine learning.
  • Demonstrated work experience C++ and python
  • Experience with Windows and UNIX development platforms.
  • Excellent written and oral communication skills, as demonstrated by term papers, technical publications, or conference presentations

For additional questions or to send your resume directly please contact career@a2ia.com or visit us at www.a2ia.com