Post Doc in Geospatial Deep Learning Applications

University of Copenhagen Department of Food and Resource Economics

Denmark

Post doc position in Geospatial Deep Learning Applications

We invite applications for a postdoctoral fellow at the University of Copenhagen, as part of a 2-year project financed by VELUX foundation as a Villum Experiment project ‘Drawing a line in the sand: Mapping sand mining in Africa for future sustainable usage’ lead by Assistant Professor Mette Bendixen in collaboration with Professor Rasmus Fensholt (Department of Geoscience and Natural Resources Management) and Professor Niels Strange (Department of Food and Resource Economics). The position is for 22 months

The candidate will work on the topic of machine learning applications for detecting landscape changes and identify sand mining activities throughout the African continent. A core role for the candidate is to build, train, and validate deep learning techniques within machine learning applied to satellite remote sensing data.

Project description

Sand and gravel make up the most extracted group of materials worldwide, even exceeding fossil fuels1 and are a key ingredient for modern civilization. But today, sand and gravel are being extracted faster than they can be replenished, and we have no knowledge of how much sand there is and where it is being mined. Meanwhile, with more people on the planet, the need for sand and gravel will continue to add pressure on the known resources. The complete lack of overview of sand mining exploration is highly understudied and has resulted in a complete gap in our knowledge of the environmental and human consequences of these activities. The project will combine landscape analyses, remote sensing imagery and deep learning to develop a data-driven method to produce a complete overview of sand mining activities in Africa to pave the way for better management of this critical resource and new research on urban development, human health, and environmental sustainability in Africa.

Job description/objectives

The employment is at the Department of Food and Resource Economics, but the scientific work will be split 50/50 between the Department of Geoscience and Natural Resource Management and the Department of Food and Resource Economics

Your key tasks as a Post doc at the SCIENCE faculty are:

  • Create an extensive training database from remotely sensed imagery for deep learning algorithm training and validation
  • Design and build a deep learning architecture and train classification algorithms
  • Publishing peer reviewed articles
  • Presenting at scientific conferences and other outreach related activities

Formal requirements/Qualifications

The candidate will have a PhD degree or equivalent doctorate, with a background in one or more of the following research fields computer science, remote sensing, geoinformatics or a closely related field. The position requires a solid background in machine learning with good knowledge on deep learning. The ideal candidate will demonstrate a working proficiency in one or more of the programming languages commonly used in data science (e.g. Python, Java, C/C++ or R) as well as deep learning frameworks (e.g. Pytorch, Tensorflow or Keras).

Also, a record of experience with data curation, image processing and the application geospatial data and geostatistical tools and a proven record in publishing peer reviewed articles is considered an advantage.

Fluency in spoken and written English is a requirement.

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 assistant Professor Mette Bendixen, Department of Geography, McGill University, Canada, mette.bendixen@mcgill.ca.

The position is open from 1st May 2022 or as soon as possible thereafter.

The University wishes our staff to reflect the diversity of society and thus welcomes applications from all qualified candidates regardless of personal background.

Terms of employment

The position is covered by the Memorandum on Job Structure for Academic Staff.

Terms of appointment and payment accord to the agreement between the Ministry of Finance and The Danish Confederation of Professional Associations on Academics in the State.

Negotiation for salary supplement is possible.

The application, in English, must be submitted electronically by clicking APPLY NOW below.

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

The deadline for applications is 25th January 2022, 23:59 GMT +1.

After the expiry of the deadline for applications, the authorized recruitment manager selects applicants for assessment on the advice of the Interview Committee.

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

Interviews will be held on 7-8 March 2022

APPLY NOW

Part of the International Alliance of Research Universities (IARU), and among Europe’s top-ranking universities, the University of Copenhagen promotes research and teaching of the highest international standard. Rich in tradition and modern in outlook, the University gives students and staff the opportunity to cultivate their talent in an ambitious and informal environment. An effective organisation – with good working conditions and a collaborative work culture – creates the ideal framework for a successful academic career.

Info

Application deadline: 25-01-2022
Employment start: 01-05-2022
Working hours: Full time
Department/Location: Department of Food and Resource Economics


In your application, please refer to Professorpositions.com

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