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Job ID: 111740

Methodology for mapping and monitoring different pasture-based livestock management and mixed crop-l
Universidade Estadual de Campinas


Date Posted Sep. 5, 2018
Title Methodology for mapping and monitoring different pasture-based livestock management and mixed crop-l
University Universidade Estadual de Campinas
Campinas, São Paulo, Brazil
Department School of Agricultural Engineering (Feagri)
Application Deadline Sep. 30, 2018
Position Start Date November 2018
 
 
  • Post-Doc
  • Land & Water Resource Engineering
    Forest Ecology & Management
    Environmental Science & Ecology
    Engineering/Engineering Extension
    Botany
    Biosystems Engineering
    Agronomy/Plant & Soil Sciences
    Agricultural Extension
    Agricultural - General
 
 

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
Job description:

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
    Selection process
    Inquiries should be directed by email to Paulo Graziano (graziano@g.unicamp.br) with a copy to NIPE project manager (Johinislan Prates, jprates@unicamp.br), 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.


 
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