Research theme area:
This research is part of the RCGI project - 64 GHG project - D.1, which has the title: “Greenhouse gas emissions in the Amazon and data analysis system and services”. In this project, a multidisciplinary team will build a computer system that integrates data associated with the emission of greenhouse gases in the Amazon, which integrate land use changes, remote sensing of greenhouse gases, meteorological parameters, forest degradation data, internal measures. in situ in soil and in fluxes and concentrations of greenhouse gases in the Amazon. The project will integrate land use change data from MapBiomas, INPE deforestation and fire detection systems, remote sensing and in-situ measurement of greenhouse gases data in an open access computational platform using machine learning and artificial intelligence techniques, with web access.
This project intends to evaluate the time-evolution of greenhouse gases (GHG) and how convection interact and modify GHG. The basic steps are the compilation of historical GHG dataset from different satellite database. There is a clear evolution on satellite hardware and processing software, the GHG bases are, most of the time, spread in different bases by satellite and algorithms. Therefore, an investigation of the broad available dataset, from NASA, Copernicus, Eumetsat, ECMWF, NOAA, AWS, among several others database need to be studied, detailed, in order to select the most appropriate dataset or combined dataset to be employed in this study. The second step is the preparation of the dataset, with includes download, reprocessing in regular space and time. The preparation of this
dataset will follow the big data concepts and will need the development of algorithm dataset-combination and time-space interpolation. This last component will be done in partnership with the computational team.
The applicant will contribute in line with the main objectives of the project:
Assembly and compilation of the CO2 and CH4 measurement database in high spatial resolution produced by several remote sensing platforms. Incorporation and integration of measurements from NASA and European Union satellites such as OCO-2 (Orbiting Carbon Observatory-2), GOSAT (Greenhouse Gases Observing SATellite), constellation of Sentinel satellites from ESA (European Space Agency), TROPOMI (TROPOspheric Monitoring Instrument) among others.
Requirements to fill the position:
This Post Doc fellowship is suitable for a highly motivated researcher with a background in physics, chemistry, engineering, computing or mathematics. Requires programming skills in MatLab or Python. Desirable knowledge of remote sensing techniques for aerosols, trace gases or land use change. English proficiency is required. Ability to collaborate and develop your work in large teams is required.
The candidate must have obtained a doctorate degree less than seven years ago, priority for candidates who have just completed the Doctorate, within the regular duration, with an excellent academic record in postgraduate studies.
INFORMATION ABOUT FELLOWSHIP:
This Postdoc fellowship is funded by FAPESP. The fellowship will cover a standard maintenance stipend of R$ 7.373,10 per month.
Position: Post-Doctoral REF: 21PDR135
https://www.rcgi.poli.usp.br/opportunities-aplication/ AND APPLICATION AT REF 21PDR135 – Post Doctoral