PML is looking for a versatile remote-sensing scientist to work on new national and international research and development projects in the PML Earth Observation science group. Current projects focus on R&D in satellite data analysis and processing methods for monitoring water quality in coastal, transitional and open-ocean water bodies from the regional up to the global scale.
Scientific areas include: high resolution remote sensing of coastal suspended particulates, eutrophication indicators and open-ocean observation of the ocean carbon cycle. The work will use 1 km and 300m optical satellite data from Sentinel 3 OLCI and 10-60m data from Sentinel 2 MSI in a cutting-edge computing environment including a recent £1M investment in a GPU-based processing cluster
The post is initially for three years, but given the on-going success of the PML EO group extension for longer duration is anticipated.
Key Deliverables
- Research and development of scientific methods dealing with: different sensors, configurations, and atmospheric and biogeochemical retrieval algorithms.
- EO product development and validation of water quality parameters and critical elements of the marine carbon cycle.
- Spatial, temporal and other statistical analyses of EO data.
- Scientific publication and reporting (including oral presentations) of results.
Experience & Eligibility Requirements
The appointment will be made at Scientist grade and candidates would possess a PhD or equivalent experience in Earth Observation, limnology, oceanography or a similar numerical field (mathematics, statistics, computing, or physics). The successful candidates will need to demonstrate strong computing skills as appropriate for quantitative remote sensing R&D (most of our software is implemented in Python) as well as numerical and mathematical skills. The post holder will work both individually and in a team, as required, be self-motivated, with good communication skills, including in scientific writing.
Closing Date: 28th January 2019
https://advanced.advorto.com/PML/Brochure/
via IFPRS