Sort by
Refine Your Search
-
Country
-
Employer
- Nanyang Technological University
- National University of Singapore
- Zintellect
- University of Bergen
- University of Idaho
- University of Notre Dame
- University of Oslo
- University of Sydney
- CRANFIELD UNIVERSITY
- Florida Atlantic University
- Hong Kong Polytechnic University
- Instituto de Geografia e Ordenamento do Território da Universidade de Lisboa
- Montana State University
- NTNU - Norwegian University of Science and Technology
- QUEENS UNIVERSITY BELFAST
- Queen's University Belfast
- UNIVERSITY OF SOUTHAMPTON
- UNIVERSITY OF SYDNEY
- University of Southampton;
- University of Texas at Austin
- University of Turku
- 11 more »
- « less
-
Field
-
modeling. Proficiency in Python and experience with AI/ML frameworks such as PyTorch or TensorFlow. Experience handling large geospatial, atmospheric, or remote sensing datasets is preferred. Strong
-
new international Master of Science (Technology) degree programme, particularly in the fields of remote sensing and geospatial computing, while also advancing research on digital waters. The position is
-
to sedimentological and biogeochemical investigations contribute to modelling sedimentary copper systems and Earth surface processes analyse and interpret large-scale geospatial and geochemical datasets publish high
-
2nd October 2026 Languages English English Norsk Nynorsk English PhD Research Fellow in Remote Sensing and modelling of alpine vegetation change Apply for this job See advertisement UiB - Knowledge
-
environment data for Singapore from government agencies and open sources, using GIS software (i.e. QGIS), R, and Python. Undertake 2D and 3D geospatial modelling and analysis. Apply spatial and statistical
-
experience developing deep learning models using frameworks using PyTorch and possess strong Python programming skills. Experience working with Remote Sensing datasets and geospatial technologies such as GDAL
-
focus on collecting, processing, and harmonising appropriate geospatial data, providing geospatial data insights, and applying appropriate AI models for geospatial analysis based on the integrated data
-
to those with: (a) strong background in quantitative methods, statistics, computer science, geospatial data analysis and modelling; (b) experience in AI and geospatial computer version; (c) advanced
-
insights, and applying appropriate AI models for geospatial analysis based on the integrated data. This role is part of the project: Decision-support-tools for Spatial Planning and Cumulative Effects
-
and quantitative models. Documented capabilities in programming like Python, R, SQL, or Julia. Proficient in Excel and PowerPoint. Preferred Qualifications Geospatial modeling and analysis is a