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Position: Research Associate for CEOI OVERPaSS (On-board VidEo Rapid ProceSSing) project
Institution: University College London
Department: Space & Climate Physics
Location: London, United Kingdom
Duties: This post is mainly concerned with research and development of a deep learning based image matching algorithm for clouds and stereo matching algorithm for processing of massive satellite data, particularly for a large number of view angle intersections for application to “point-and-stare” video systems to generate dense point clouds. In addition, the applicant would be expected to collaborate with other members of the Imaging group working on machine vision and deep learning applications to EO and planetary datasets
Requirements: The postholder will be expected to have a PhD in computer vision and deep learning preferably related to airborne or satellite data or equivalent work experience. Programming experience (in C++ and/or Python) for EO stereo satellite data, knowledge of deep learning and computer vision, knowledge of stereo photogrammetry, and knowledge of linux are also essential requirements for this post
   
Text: Research Associate for CEOI OVERPaSS (On-board VidEo Rapid ProceSSing) project, - Ref:1736020 Click here to go back to search results Apply Now UCL Department / Division Space & Climate Physics Location of position Dorking Grade 7 Hours Full Time Salary ?31,604 to ?32,548 per annum Duties and Responsibilities An exciting opportunity have arisen for a Research Associate to join Prof. Jan-Peter Muller?s Imaging Group in the Department of Space and Climate Physics. The postholder will work on a project funded by the UK Space Agency CEOI (Centre for Earth Observation Instrumentation) through a contract managed by Earth-i. Prof. Muller?s Imaging group is engaged in developing, processing and validating climate quality global datasets (including BRDF/albedo, wind and cloud properties), primarily from EO sensors, for inter-comparison with other planets, such as Mars and in the analysis of Sun-planetary connections to planetary climate. This post is mainly concerned with research and development of a deep learning based image matching algorithm for clouds and stereo matching algorithm for processing of massive satellite data, particularly for a large number of view angle intersections for application to ?point-and-stare? video systems to generate dense point clouds. In addition, the applicant would be expected to collaborate with other members of the Imaging group working on machine vision and deep learning applications to EO and planetary datasets. MSSL is a multi-disciplinary laboratory, with a long track record in the design, build, operation and exploitation of EO, space and astrophysics instrumentation. MSSL was selected by ESA to develop the CRYOSAT instrument and is currently involved with a number of Sentinel missions. Prof. Muller has been a member of the NASA EOS MODIS and MISR science teams since 1990 responsible for the development of the operational multi-angle retrieval of surface BRDF/albedo and cloud-top and aerosol-top heights and winds. This is a full-time post that is available until 30 June 2021 in the first instance. Key Requirements The postholder will be expected to have a PhD in computer vision and deep learning preferably related to airborne or satellite data or equivalent work experience. Programming experience (in C++ and/or Python) for EO stereo satellite data, knowledge of deep learning and computer vision, knowledge of stereo photogrammetry, and knowledge of linux are also essential requirements for this post. Further Details A job description and person specification can be accessed at the bottom of this page. To apply for the vacancy please click on the ?Apply Now? button below. Informal enquiries should be made to Yu Tao ( yu.tao@ucl.ac.uk ). If you are having difficulty accessing the on-line recruitment system please contact Mrs Suzanne Winter ( s.winter@ucl.ac.uk ) for advice. UCL Taking Action for Equality We will consider applications to work on a part-time, flexible and job share basis wherever possible. Closing Date 16 Aug 2018 Latest time for the submission of applications 23:59 Interview date TBC This role does not meet the eligibility requirements for a tier 2 certificate of sponsorship under UK Visas and Immigration legislation. Therefore UCL will not be able to sponsor individuals who require right to work in the UK to carry out this role. This appointment is subject to UCL Terms and Conditions of Service for Research and Support Staff. Please use these links to find out more about the UCL Terms and Conditions related to this job, employee benefits that we offer and further information about UCL . Job Description and Person Specification Apply Now
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