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/C++, FORTRAN and/or Python. Experience working with geo-spatial information, remote sensing data, and GIS software. Experience in deep learning and computer vision. Experience in developing software
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of dendrochronology techniques, from the research plan, field work and laboratory, and interpretation and publication. He/she should be comfortable with the R and/or Python languages. Experience in handling large
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years prior to the effective date of appointment with a minimum of one year eligibility remaining. • Strong proficiency in Python or R and experience with High-Performance Computing. • Proficient
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modelling tools are required. Robust modelling and programming abilities (e.g., Python) are essential prerequisites. Experience with VIC (or similar hydrologic models), GIS, and large-scale computing
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; GIS software; spatial analysis and visualization; programming in R, Python, or similar; quantitative data collection and analysis; scientific synthesis and writing. Experience partnering with non
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Andres Masegosa (arma@cs.aau.dk), Department of Computer Science. (please see: https://andresmasegosa.github.io/ . The project’s domain PI is Professor Jamal Jokar Arsanjani (jja@plan.aau.dk), Department
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, geospatial analyses and/or statistical modelling, satellite data retrieval; preferably experience with Pascal programming language and R or Python and geographic information systems (GIS); a proactive attitude
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Date: As soon as possible Group or Departmental Website: https://naturalcapitalproject.stanford.edu/ (link is external) How to Submit Application Materials: Send an email with your attachments