AISB convention 2017

  In the run up to AISB2017 convention, I've asked Joanna Bryson, from the organising team, to answer few questions about the convention and what comes with it. Mohammad Majid al-Rifaie (https://twitter.com/mohmaj) Tu...


Read More...

Harold Cohen

Harold Cohen, tireless computer art pioneer dies at 87   Harold Cohen at the Tate (1983) Aaron image in background   Harold Cohen died at 87 in his studio on 27th April 2016 in Encintias California, USA.The first time I hear...


Read More...

Dancing with Pixies?...

At TEDx Tottenham, London Mark Bishop (the former chair of the Society) demonstrates that if the ongoing EU flagship science project - the 1.6 billion dollar "Human Brain Project” - ultimately succeeds in understanding all as...


Read More...

Computerised Minds. ...

A video sponsored by the society discusses Searle's Chinese Room Argument (CRA) and the heated debates surrounding it. In this video, which is accessible to the general public and those with interest in AI, Olly's Philosophy Tube ...


Read More...

Connection Science

All individual members of The Society for the Study of Artificial Intelligence and Simulation of Behaviour have a personal subscription to the Taylor Francis journal Connection Science as part of their membership. How to Acce...


Read More...
01234

Notice

AISB opportunities Bulletin Item

Post-Doctoral Research Fellowship on Similarity-based Pattern Recognition at University of Verona


Post-Doctoral Research Fellowship on Similarity-based Pattern Recognition at University of Verona (Italy)

The Vision Image Processing & Sound (VIPS) laboratory of the University of Verona (Italy) invites applications for one full time postdoctoral research fellowship to undertake research on similarity-based Pattern Recognition. The successful candidate will work in the context of SIMBAD project (Beyond Features: Similarity-Based Pattern Analysis and Recognition), a 3 year EU FP7-funded FET (Future & Emerging Technology) project involving European Universities leaders in the field of Pattern Recognition and Computer Vision. The overall project aims at developing new methods for pattern analysis and machine learning based on potentially non-metric similarity data (more info at http://simbad-fp7.eu/).

Candidates should have a PhD in Computer Vision and/or Machine Learning/Pattern Recognition (or at least have submitted the thesis and awaiting the viva). Additional requirements include strong experience in programming and a good research record.
The postdoctoral position is for 1 year renewable for 3 years

Starting Date.
1 March 2009

Salary and Fringe Benefits.
The salary will be about 22,000  per annum (gross salary). Based on the qualification of the candidate, an additional grant to partially cover the lodging in Verona according to the local costs will be given.

Application Procedure
Applications must be received by 30th of January 2009.
Applicants should submit a CV listing all publications (please indicate in the CV three independent references). The pdf files of the most representative publications are also required. Finally, applicants should submit a research statement, describing previous research experiences with emphasis on the possible relevance to the SIMBAD project.


Further details and informal enquiries can be made by email to Prof Vittorio Murino: vittorio.murino@univr.it and Dr Manuele Bicego: manuele.bicego@univr.it.

--------------------------------------------------------

The Vision,  Image Processing, & Sound (VIPS) Laboratory is one of Italys leading research laboratories in Computer Vision and Pattern Recognition, headed by Prof. Vittorio Murino (http://vips.sci.univr.it/) within the Department of Computer Science of the University of Verona.
The lab currently undertakes research on statistical Pattern Recognition, with theoretical emphasis on generative-discriminative modelling and practical relapses on video-surveillance and scene
understanding, bioinformatics, 3D geometrical modelling, scene and object representation, reconstruction, and retrieval.