Research Associate in Data Science
31 January 2017
We are seeking an excellent postdoctoral researcher in signal processing, applied mathematics, physics, statistics, computer science, or a related field, to develop novel signal analysis techniques for extracting scientific information from large observational data-sets. Research aims will include a focus on signal analysis on the sphere but can be extended to incorporate the interests and expertise of the successful applicant.
Signals defined on the sphere are prevalent in a diverse range of fields, including cosmology, geophysics, acoustics, and computer graphics, for example. In cosmology, observations made by the European Space Agency’s Planck and Euclid satellites live on the celestial sphere, leading to very large and precise spherical data-sets, the robust analysis of which can reveal a great deal about the nature of our Universe. The successful applicant will focus on the theoretical and methodological foundations of the analysis of signals defined on the sphere and will work closely with another postdoctoral researcher who will fill a complementary post focused on application to observational data.
The successful applicant will be based in the Astrophysics Group at the Mullard Space Science Laboratory (MSSL) of University College London (UCL) and will join the multi-disciplinary astroinformatics team, which comprises researchers with expertise in astrophysics, applied mathematics, signal processing, statistics and software engineering. The goal of the astroinformatics team is to develop and apply novel analysis techniques to extract scientific information from very large data sets, in order to develop a deeper understanding of the fundamental physics underlying the evolution of our Universe. The successful applicant will work closely with Dr Jason McEwen, while also interacting with other members of the astroinformatics team and the Astrophysics Group.
Closing date for applications is 25 February 2017.
A Job and Person Specification is available to download
To apply for this post please go to: http://www.ucl.ac.uk/hr/jobs/ and search on 1625644.
Page last modified on 31 jan 17 15:49