Research Fellow in Data Science Ref 2980
School/department: School of Mathematical and Physical Sciences
Hours: full time
Contract: fixed term for 10 months
Salary: starting at £32,548 and rising to £38,833 per annum
Placed on: 13 February 2018
Closing date: 4 April 2018. Applications must be received by midnight of the closing date.
Expected interview date: 13 April 2018
Expected start date: 1 May 2018
The University of Sussex invites applications for a Postdoctoral Research Fellow to apply advanced data science and machine learning techniques used in astronomy to Earth Observations facilitating improved hazard early warning models in Kenya.
This pilot project is funded by the Science Technology and Facilities Council (STFC) as part of the Global Challenges Research Fund.
You will be part of an interdisciplinary team of astronomers and climate and land change scientists.
This project will use data from the Copernicus Sentinel mission (data provided every 5-12 days at 10-20m resolution) with 13 spectral bands including three red-edge bands providing key information on vegetation state.
The activities in this pilot will be
- to develop, calibrate and bench-mark new tools for land-use classification from multi-spectral remote sensing data
- to develop new techniques for temporal characterisation (phenology) of remote-sensing data and identification of atypical change-points in usage or yields
- to provide a prototype for an empirical forecasting model
You will be someone who has the imagination and technical skills to find creative, collaborative solutions to these important challenges.
You will work within the Data Intensive Science Centre http://www.sussex.ac.uk/discus/, the Astronomy Centre, http://www.sussex.ac.uk/astronomy/ and as part of the Schools of Mathematical and Physical Sciences, and Global Studies (ranked number 1 in the world for development studies in QS 2016/2017).
Enquiries should be addressed to Prof. Seb Oliver (S.Oliver@Sussex.ac.uk).
Candidates should complete an application form and include a CV and a statement of research interests and skills with their application.
How to apply
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