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Scientific activities / projects

Analysis of social media data

Starting date

immediately

Duration of contract

3 years

Remuneration

up to the German TVöD 14

Type of employment

Full-time

"Cutting-edge research requires excellent minds – particularly more females – at all levels. Launch your mission with us and send in your application now!" Prof. Pascale Ehrenfreund - Chair of the DLR Executive Board

The department “EO Data Science” at the Remote Sensing Technology Institute (IMF-DAS), located at the DLR in Oberpfaffenhofen near Munich is developing novel signal processing and AI algorithms to improve information retrieval from remote sensing data, in particular those from current and the next generation of Earth observation missions and deliver crucial geo-information to address social grant challenges, such as urbanization and climate change. In the framework of the project „So2Sat: Big Data for 4D Global Urban Mapping – 1016 Bytes from Social Media to EO Satellites“ methods to allow a four dimensional mapping of the urban areas and population dynamics should be developed by fusion of social media and earth observation data.

The holder of the position will be responsible for the development of innovative algorithms for analyzing social media data in combination with earth observation data:

  • statistical analysis of social media data to estimate the information content
  • development of new and advanced algorithms for unsupervised analysis and extraction of information from social media data (i.e. Twitter messages or photos)
  • conception and development of algorithms for the assignment of Social media data on the places of their creation (at city and building level)
  • new and further development of  methods for infrastructure classification based on features extracted from social media data
  • conception and development of methods for the fusion of the classification results obtained from social media data with classification results obtained with established methods from satellite imagery
  • implementation of the procedures in prototype algorithms
  • detailed documentation of the implemented software modules
  • conception, implementation and maintenance of an Internet platform for so-called "Volunteered Geographic Information" (VGI), in order to generate an additional data source for
  • scientific investigations in the project
  • presentation of the research results to the scientific community, i.e. by publishing in high-level journals and presentations at international conferences

Your qualifications:

  • completed academic studies (university diploma / master) in computer science, mathematics, statistics or a comparable subject
  • doctorate in data processing or machine learning, ideally related to social media data
  • experience in scientific analysis and machine processing of social media data (especially photos and text messages)
  • experience in machine learning
  • very good programming skills in a development language (IDL, Matlab, Python) or C/C ++
  • very good knowledge of spoken and written German
  • good written and spoken English knowledge
  • experience in handling geodata is an advantage
  • experience in the supervising junior scientists/PhD students is a plus

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.

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Technical contact

Prof. Dr. Ing. Xiaoxiang Zhu
Remote Sensing Technology Institute

Phone: +49 8153 28-3531

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Vacancy 46517

HR department Oberpfaffenhofen

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DLR site Oberpfaffenhofen

To location

DLR Remote Sensing Technology Institute

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