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Postdoc position in Remote Sensing of Vegetation -UCPH, Denmark

University of Copenhagen (UCPH)

Denmark

Postdoc position in “Remote Sensing of Vegetation” at the Department of Geosciences and Natural Resource Management (IGN) within the Section for Geography, Faculty of Science, University of Copenhagen – Denmark, Oct 2021

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General Info

Position: Postdoc
No. of Positions: 1
Research Field:
Deadline to Apply: Expired
Joining Date: Nov 01, 2021 or ASAP
Contract Period: 2 Years
Salary: According to Standard Norms

Workplace:
Faculty of Science
Department of Geosciences and Natural Resources Management,
University of Copenhagen (UCPH)
Copenhagen K,

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Qualification Details

Not Mentioned

Responsibilities/Job Description

The postdoc’s duties will include research within the field of Remote Sensing as well as teaching. The post may also include performance of other duties.

How to Apply?

Online Application through "Apply Now" Button from this page or from advertisement webpage (URL below)

Reference Number: -
(If any, use it in the necessary place)

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Documents Required

Please include

  • Curriculum vitae
  • Diplomas (Master and PhD degree or equivalent)
  • Research plan – description of current and future research plans
  • Complete publication list
  • Separate reprints of 3 particularly relevant papers

About the Project

Mitigating climate change while securing livelihoods is a major societal challenge in the 21 st century. In this context, trees and shrubs (hereafter collectively referred to as trees) play a key role, as trees constitute a stable carbon sink while providing ecosystem services to the local population. Quantifying and monitoring the world’s trees is thus of highest importance, however, current assessments and statistics focus on trees within forests, overlooking trees outside forests. The extent of non-forest trees has thus never been systematically assessed at large scale, so it has never been possible to study their impact on biochemical cycles as well as their economic or ecological importance at large scales. This project builds on two revolutionary developments impacting on the field of remote sensing which allow the mapping and monitoring of individual trees outside forests in great details at a continental scale, introducing variables that go beyond woody cover and opening new perspectives for research in the context of ecosystem services. First, the massive increase in available data with petabytes of images recorded by satellites every year. Second, machine learning has been shown to deliver excellent results in the field of object segmentation in high resolution satellite images, as well as studying ecosystem patterns and dynamics in relation to climate change. The post doc will develop and work with continental scale data sets to study changes in tree cover, vegetation and related variables in relation to climate change. The candidate must have proven to be able to work with large scale environmental datasets. Python programming skills are required.

Further information on the Department is linked at https://www.science.ku.dk/english/about-the-faculty/organisation/. Inquiries about the position can be made to Martin Brandt.

About the Employer: University of Copenhagen (UCPH)

Note or Other details

You can read about the recruitment process at https://employment.ku.dk/faculty/recruitment-process/.

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Contact details

Inquiries about the position can be made to Martin Brandt.

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