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Title: Postdoctoral Fellowship : Methodology for mapping and monitoring different pasture-based livestock management and mixed crop-livestock systems with remote sensing
Location: School of Agricultural Engineering (Feagri), State University of Campinas (Unicamp), Brazil
The successful candidate will develop, test and apply remote sensing analysis techniques to map and monitor pasture and mixed crop-pasture systems in western São Paulo state, Brazil. The successful candidate will:
carry out a review of different methods of agricultural intensification taking into account crop and livestock association aspects;
identify different algorithms for classifying distinct pasture managements;
explore the possibilities of identifying natural and intensified pasture and mixed crop-livestock systems using time-series data from different sensors;
develop digital image classifiers using time-series imagery with machine learning algorithms to map different types of crop-livestock systems;
build models (biomass x remote sensing data)
The post-doc is part of the FAPESP – (FAPESP 2017/50205-9) " Monitoring integrated crop-livestock systems through remote sensing and precision agriculture for more sustainable production – Towards Low Carbon Agriculture". Several laboratories and institutions collaborate in this project, such as Interdisciplinary Center for Energy Planning (NIPE) and the School of Agricultural Engineering – Feagri (UNICAMP), Embrapa Agricultural Informatics, Universidade do Oeste Paulista – Unoeste, and the Delft University of Technology – TUDelft.
The post-doc will be under the supervision of Professor Jansle Rocha and will collaborate with the different researchers involved in the project.
The fellowship includes a taxfree monthly stipend of R$ 7.174,80, plus 15% of the yearly value for research related expenses. All conditions and salary related to this FAPESP post-doc are listed there : http://www.fapesp.br/en/postdoc.
Desired skills and competence
A Ph.D. in engineering/earth sciences/ geography/ agronomy, with applications of remote sensing;
Experience on time series, advanced digital image processing and analysis of remotely sensed data. Experience with radar imagery will be a bonus;
Experience in field data collection/measurements;
Working knowledge of coding languages (ex: Matlab, R, Phyton, etc. ) and data analysis techniques . Advanced skills in R and machine learning will be considered an asset;
Minimum qualifications include a demonstrated ability to publish peer-reviewed papers, effective oral communication skills, and to work well in a collaborative team environment.
Strong interpersonal skills and adequate fluency in English, Portuguese will be a bonus
Full-time work, 1 year, starting in November 2018
All conditions and salary related to this FAPESP post-doc are listed there : http://www.fapesp.br/en/postdoc
Inquiries should be directed by email to Paulo Graziano (firstname.lastname@example.org) with a copy to NIPE project manager (Johinislan Prates, email@example.com), including "FAPESP project 2017/50205-9 post-doc PD2" in the subject line until September 30st, 2018.
Send a cover letter stating your professional experiences and how you would satisfy the minimum qualifications (2 pages max), a CV, and two recommendations letters (all documents in pdf format).
Submissions by email until September 30th , 2018.
Please reference AcademicKeys.com in your cover letter when
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