[Neuroinfo] Postdoctoral position in Pattern Recognition, Machine Learning and Computer Vision for the analysis of retinal electrophysiology in response to visual stimulation, with specific expertise in deep learning and sparse learning BC: 71326 - 71327

[Diego Sona]

Postdoctoral position in Pattern Recognition, Machine Learning and Computer Vision for the analysis of retinal electrophysiology in response to visual stimulation, with specific expertise in deep learning and sparse learning

BC: 71326 - 71327

Fondazione Istituto Italiano di Tecnologia – IIT – was established by the Italian government to promote technological development and training in the scientific and technological field. Toward this end, IIT is implementing a detailed scientific program, which comprises integration across fundamental research and application. IIT’s research endeavour focuses on high-tech and innovation, representing the forefront of technology with possible application from medicine to industry, computer science, robotics, life sciences and nano-biotechnologies.
One postdoctoral position in Computer Vision, Pattern Recognition and Machine Learning is available in the department of Pattern Analysis and Computer Vision (PAVIS) at the Istituto Italiano di Tecnologia (IIT) ,Genova, Italy.

PAVIS department has consolidated expertise in image processing, computer vision, pattern recognition and machine learning and aims at studying and designing intelligent systems for the analysis and understanding of real-world problems. PAVIS focuses in particular on activities related, but not limited, to surveillance and security, biomedical imaging, and bioinformatics.

Project Description
The research position is funded by the European project “RENVISION - Retina-inspired ENcoding for advanced VISION tasks” (http://www.renvision-fp7.eu/ <http://www.renvision-fp7.eu/>). The overall aim of the project is to achieve a comprehensive understanding of how the retina encodes complex visual scenes, and to use such insights to develop new computational models of retina and toapply them to high-level computer vision tasks, such as scene categorization and action recognition. The project is highly interdisciplinary, including neuro-engineering, electrophysiology, high-resolution microscopy imaging, computational modelling, data analysis, machine learning and computer vision.
RENVISION is funded by the European Commission FP7 Future Emerging Technologies programme, under contract n. 600847.

Description of the research
The candidate will design novel methodologies and algorithms based on pattern recognition and machine learning techniques, aiming at analysing electrophysiological recordings in response to visual stimulation of retina.  The main objective of the research is the discovery/determination of representative and/or discriminative features in retina coding allowing for high-level vision tasks, such as scene categorization and action recognition. To this purpose, deep learning, sparse and dictionary learning approaches are to be considered.

Experience and Qualifications
We are seeking a self-motivated individual with the ability to take day-to-day responsibility for the progress of the proposed work. The ideal candidate will have a PhD in Computer Science, Mathematics, Electronic Engineering or a closely-related discipline, with competences on machine learning/pattern recognition/computer vision, coupled with a keen interest in neuroscience and biological data processing and analysis. Expertise in deep learning, compressive sensing, and/or dictionary learning is in general preferred. Experience in spiking networks or retinal function will be appreciated while not being a discriminating factor. A strong programming skill is required.
Annual salary will depend on research experience and qualification.

Closing Date
The initial deadline for applications is September 7th , 2015, however please note that the search will continue until appropriate candidates have been identified.

How to apply
Completed application forms along with a curriculum listing all publications (possibly including pdfs of the most representative ones), names of 2 referees and a research statement (describing previous research experience and outlining its relevance to the above topics) should be sent by email to Prof. Vittorio Murino vittorio.murino at iit.it <mailto:vittorio.murino at iit.it> and/or Diego Sona  diego.sona at iit.it <mailto:diego.sona at iit.it>, quoting PAVIS-PD 71327 – 71326 as reference number.

For informal enquiries please write to Prof. Vittorio Murino vittorio.murino at iit.it <mailto:vittorio.murino at iit.it> or Diego Sona  diego.sona at iit.it <mailto:diego.sona at iit.it>.

In order to comply with Italian law (art. 23 of Privacy Law of the Italian Legislative Decree n. 196/03), the candidate is kindly asked to give his/her consent to allow Istituto Italiano di Tecnologia to process his/her personal data.
We inform you that the information you provide will be solely used for the purpose of evaluating and selecting candidates in order to meet the requirements of Istituto Italiano di Tecnologia.
Your data will be processed by Istituto Italiano di Tecnologia, with its headquarters in Genoa, Via Morego 30, acting as the Data Holder, using computer and paper-based means, observing the rules on the protection of personal data, including those relating to the security of data, and they will not be communicated to thirds.
Please also note that, pursuant to art.7 of Legislative Decree 196/2003, you may exercise your rights at any time as a party concerned by contacting the Data Holder.
Istituto Italiano di Tecnologia is an Equal Opportunity Employer that actively seeks diversity in its workforce



Diego Sona

---------------------------------------------------------
Pattern Analysis & Computer Vision (PAVIS)
Istituto Italiano di Tecnologia (IIT)
Via Morego 30, 16163, Genova, Italy

Phone:	+39 010 71781 819
E-mail:	diego.sona at iit.it <mailto:diego.sona at iit.it>
		www.iit.it/pavis.html <http://www.iit.it/pavis.html>
---------------------------------------------------------
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://lists.incf.org/pipermail/neuroinfo/attachments/20150831/f50656f3/attachment-0001.html>