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  3. Assistant Professor in Big Data Science for Natural Resources

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Assistant Professor in Big Data Science for Natural Resources

You will develop high-quality research and educational methods and outputs focusing on the handling, processing and upscaling of large volumes of spatial and …

ongeveer een maand geleden


Drienerlolaan, Enschede, Overijssel
Tijdelijk contract / Tijdelijke opdracht
Uren per week:
40 - 40 uur
€ 3746 - € 5127 per maand


You will develop high-quality research and educational methods and outputs focusing on the handling, processing and upscaling of large volumes of spatial and temporal information. This information comes from diverse sources including lab, field, remote sensing and online data harvesting. You will work at regional, continental and global levels to monitor natural and agricultural systems. You have expertise in Artificial Intelligence approaches for mining data and are comfortable developing large database applications for forest and (semi-) natural area ecosystem structure & ecosystem function, estimating above ground biomass & carbon density, and deriving crop productivity parameters.

You will contribute to research on big data applications in natural resources management (using both structured and unstructured data), to grant/project acquisition, and to project deliverables related to the department’s research themes and geographic focus areas. You will be our point of contact with ITC's Centre of Expertise in Big Geodata Science. You will teach and further develop MSc courses, given in face to face and distance learning modes.

You are excited to work in an international team with project activities around the world. You combine a drive for scientific quality and rigour with making a difference in global environmental issues. You enjoy collaborating to develop high-quality research outputs that demonstrate the societal impact of big data science. You embrace Open Science. You have a passion for education and can teach topics such as the theory and practice of big data and advanced computer processing algorithms. You are exited to develop applications for accessing and processing of large data for natural resource management. You are a dedicated supervisor for MSc and PhD students.


You have:

  • A doctoral degree related to handling and processing big data for environmental and agricultural applications at regional and global levels
  • A background in the development of methods and applications in natural resources with a focus on handling big data, artificial intelligence and machine learning
  • Recent and relevant high-quality publications in international journals in the topic areas of the job description
  • An aptitude for teaching at Master or Bachelor levels in English
  • Competency in working with multiple of the following platforms/languages (e.g. R, Python, IDL, MATLAB, C++, Java)
  • Experience with scaling up or out through multi-core and distributed computing techniques for large-scale processing of Earth observation data
  • Experience in undertaking international project work and enthusiasm to work in all regions where ITC is active
  • Excellent interpersonal skills
  • Enthusiasm to work in a range of international and interdisciplinary contexts
  • An excellent command of English

The following are an advantage but can also be developed over time.

  • Experience with collaborative projects, like EU or ESA projects, and working in international environments
  • Experience in online/distance learning modes of education
  • Knowledge of, or willingness to learn Dutch
  • A university teaching qualification


We offer an inspiring and challenging international environment. You will be initially employed for four years. Prolongation of the contract after this period is a possibility.

  • Gross monthly salary between € 3,746.- and € 5,127.- (depending on experience and qualifications, job profile Assistant Professor level 2)
  • A holiday allowance of 8% of the gross annual salary and a year-end bonus of 8.3%
  • Excellent support for research and facilities for professional and personal development
  • A solid pension scheme
  • Minimum of 41 holiday days in case of fulltime employment
  • Possibilities to save up holidays for sabbatical leave
  • Professional and personal improvement programmes