Research Associate

King's College London - Geography

The salary will be paid at Grade 6, £33,518 to £36,613 per annum based on experience, plus £2,923 per annum London Allowance.

This post will be Fixed term for 15 months in the first instance, with possible extension; pending a contract renewal for this part of the CAMS service.

This post is offered on a Full time contract.

Based at the Strand Campus, the post will be based within the research team of Prof. Martin Wooster and is focused on  further development of the Global Fire Assimilation System (GFAS), a state-of-the-art fire emissions estimation system currently operated in real-time as part of the Copernicus Atmosphere Monitoring Service (CAMS: www.gmes-atmosphere.eu). GFAS uses satellite Fire Radiative Power (FRP) data to deliver daily, global fire emissions information to CAMS, as detailed in Kaiser et al. (2012): doi:10.5194/bg-9-527-2012. The work has both high visibility and the potential for very significant impact as the results may be implemented operationally within GFAS/CAMS.

Primary foci will be on developments needed to enable new satellite FRP data steams to be used within CAMS, from both polar-orbiting (SLSTR, VIIRS etc) and geostationary (Meteosat, GOES, etc) systems. FRP data must be evaluated, blended, re-gridded and have their quality monitored to be used within GFAS, ultimately delivering enhanced, higher temporal resolution fire emissions information. The newly updated GFAS outputs will be used in science studies, and the post holder will compare the fire activity and fire emissions data to potentially influencing information on weather and vegetation conditions to help elucidate processes influencing fire activity at landscape/regional scales.

Applicants should have expertise in working with satellite remote sensing data and derived products, have algorithm development experience, be very comfortable writing well documented code in Python, and be able to work to deadlines. Some experience of biomass burning and/or other emissions research maybe beneficial.

Applicants should have strong experience of working with satellite data/products and be able to code in Python and/or IDL. Experience of working with a combination of datasets to investigate particular environmental phenomena will be a significant advantage, in order to develop definitive records of particular biomass burning episodes.

The selection process will include a panel interview.

For an informal discussion to find out more about the role please contact Prof Martin Wooster at martin.wooster@kcl.ac.uk.

To apply for this role, please go to the King’s College London HireWire Job Board and register to download and submit the specified application form.

The deadline for applications is midnight on 5 December 2017.

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