Sort by
Refine Your Search
-
Listed
-
Country
-
Employer
- MOHAMMED VI POLYTECHNIC UNIVERSITY
- Stanford University
- THE UNIVERSITY OF HONG KONG
- TTI
- Texas A&M University
- Utrecht University
- Aarhus University
- Durham University
- East Carolina University
- Nature Careers
- Ohio University
- Texas A&M AgriLife
- Texas A&M University System
- The Ohio State University
- The University of Memphis
- University of Cincinnati
- University of Illinois at Urbana Champaign
- University of Maine
- University of Maryland
- University of Minnesota
- University of Nevada, Reno
- University of New Hampshire – Main Campus
- University of Oregon
- University of Texas at Austin
- University of Washington
- Université Savoie Mont Blanc
- Université de Caen Normandie
- 17 more »
- « less
-
Field
-
: • PhD in Geography (Remote Sensing, Geomatics), Computer Science, Agricultural Sciences • Skills and/or knowledge in artificial intelligence (Machine Learning) and programming: proficiency in Python
-
for simulating river network dynamics, such as R, Julia, Python, or GIS-based hydrological modeling platforms. Ability to integrate physical, chemical, and biological components into the river-lake network models
-
develop an end-to-end processing system as well as a hazard map visualization (Web and/or GIS); Publishing the various scientific advances in conferences and peer-reviewed journals. Where to apply E-mail
-
programming languages/software such as MATLAB, Python, R, Stata, as well as GIS applications (e.g., QGIS). Have excellent communication skills in both English and Chinese, in writing and in oral presentations
-
record of publications in relevant fields. Have proficiency in data processing and statistical analysis, with experience in programming languages/software such as MATLAB, Python, R, Stata, as well as GIS
-
background in machine learning, predictive modeling, or applied AI Proficiency in Python and/or R; experience with libraries like scikit-learn, XGBoost, TensorFlow. -Experience working with real-world datasets
-
to offer. Qualifications: Required: PhD in ecology by start date Experience in plant phenology, biogeography, and spatial and temporal modeling (Bayesian and frequentist) Expertise in R or Python, GIS, big
-
data Experience with GIS/RS and database environments (e.g., ArcGIS and Quantum GIS) Experience with machine learning and statistical learning Experience working with large, diverse datasets Familiarity
-
expertise in forest ecology, disturbance ecology, and landscape ecology, and methodological expertise in harmonizing distinct databases (e.g., forest inventory, remote sensing, land cover), GIS, and R-based
-
, dynamic mapping, mobile application development, spatial data analysis, visualization, and GIS. The Lab conducts interdisciplinary collaborative projects with research partners on campus at the UO, with