Sort by
Refine Your Search
-
Listed
-
Country
-
Employer
- Zintellect
- Nanyang Technological University
- University of Oslo
- Florida Atlantic University
- Harvard University
- Instituto de Geografia e Ordenamento do Território da Universidade de Lisboa
- National University of Singapore
- The University of Queensland
- University of Bergen
- University of Notre Dame
- University of South Carolina
- University of Texas at Austin
- University of Turku
- 3 more »
- « less
-
Field
-
Engine, Python, and GIS software. Strong quantitative and analytical skills in working with satellite observations, geospatial datasets, and environmental data. As the position requires collaboration and
-
stations, including communications setup (satellite, radio, or cellular). Proficiency in data analysis using Python or R and familiarity with geospatial tools such as GIS and remote sensing datasets (LiDAR
-
will demonstrate: A Masters or PhD in engineering, environmental science, or a closely related discipline Strong analytical and numerical capability, including experience with modelling, GIS and coding
-
applying statistical or analytical methods using software such as R, SAS, Python, Stata, or similar tools. Familiarity with public health surveillance systems, environmental health data, geographic
-
. Contribute to geospatial epidemiology analyses using GIS-linked eRegistry data. Develop reproducible R-based analysis pipelines, including support for DataSHIELD or other privacy-preserving/distributed
-
, or extreme weather impacts on health. Experience with quantitative datasets and applying statistical or analytical methods using software such as R, SAS, Python, Stata, or similar tools. Familiarity with
-
collaborators. These deployments provide a rare opportunity to construct digital twins grounded in operational infrastructure, live data, and scalable computation. This position is not focused on conventional GIS
-
, perinatal, neonatal and child outcomes related to poverty-related infectious diseases. Contribute to geospatial epidemiology analyses using GIS-linked eRegistry data. Develop reproducible R-based analysis
-
statistics. Knowledge/Skills/Abilities A high level of skill in GIS, computer modeling, data analysis using SAS. Good working knowledge of programming languages VB, R, or Python. Knowledge about coastal