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Understanding snow and sea ice properties at microwave frequencies for remote sensing applications

Bremen, Germany, DLR Institute of Space Systems [DLR-USSIPMFRSADM]

Field(s) of expertise
Telecommunications Engineering
Job type
Contract
Education
DoctorateMaster
Deadline
Closed

About this job

The SAR Oceanography Team at the “Maritime Safety and Security Lab” in Bremen develops algorithms that extract and make available to users in near-real-time information on the condition of the oceans. This information is derived from radar images collected by a variety of satellites.

Your benefits:

Look forward to a fulfilling job with an employer who appreciates your commitment and supports your personal and professional development. Our unique infrastructure offers you a working environment in which you have unparalled scope to develop your creative ideas and accomplish your professional objectives. Our human resources policy places great value on a healthy family and work-life-balance as well as equal opportunities for persons of all genders (m/f/non-binary). Individuals with disabilities will be given preferential consideration in the event their qualifications are equivalent to those of other candidates.

Responsibilities

  • In the framework of the project MOSAiCmicrowaveRS will develop new and improve current methods to derive sea ice properties from microwave observations, in particular ice type and lead distribution from SAR and snow properties and ice type from microwave radiometers.
  • The project is part of the international consortium of the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) and will provide an extensive opportunity of international collaborations.
  • The PhD thesis will be supervised by Dr. Suman Singha (DLR) and Dr. Gunnar Spreen (Institute of Environmental Physics, University of Bremen).

Profile

  • Master’s degree in the field of computer science, physics, mathematics, electrical engineering or similar
  • very good Programming skill in Python and others such as IDL, C++ or similar
  • very good English language skills
  • willingness to travel and research stays at collaborative institutes
  • basic knowledge in Earth observation, ideally with synthetic aperture radar (SAR)
  • knowledge in the field of artificial intelligence and machine learning

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