Sort by
Refine Your Search
-
Listed
-
Category
-
Country
- United States
- United Kingdom
- Netherlands
- France
- Germany
- Sweden
- Portugal
- Denmark
- Belgium
- Switzerland
- Canada
- Czech
- Austria
- Finland
- Italy
- Norway
- Australia
- Singapore
- Spain
- United Arab Emirates
- Morocco
- Estonia
- Hong Kong
- Ireland
- Romania
- Japan
- Poland
- Taiwan
- Brazil
- China
- Croatia
- Cyprus
- Greece
- Lithuania
- Luxembourg
- Macau
- 26 more »
- « less
-
Program
-
Field
- Computer Science
- Biology
- Medical Sciences
- Economics
- Engineering
- Earth Sciences
- Mathematics
- Science
- Environment
- Social Sciences
- Materials Science
- Arts and Literature
- Humanities
- Chemistry
- Business
- Linguistics
- Design
- Electrical Engineering
- Education
- Psychology
- Sports and Recreation
- Physics
- 12 more »
- « less
-
starts. Preferably, you will also have: Interest in global water issues and earth system modelling; Strong quantitative methodological skills, for instance knowledge of (spatial) data analysis
-
machine learning models. ● Prior experience using spatially distributed hydrologic models, specifically those with snow mass and energy balance components Minimum Qualifications: Requires a minimum of a
-
using deep learning or causal learning methods. Candidates must have solid experience with large spatial and temporal datasets, large model manipulation, and HPC. The candidate must also have experience
-
to improve process-based understanding of infiltration dynamics in nature-based stormwater solutions by combining field monitoring, experimental investigations, and modelling. The project focuses on spatially
-
of Minnesota. U-Spatial is a nationally recognized model that provides consulting services and drives a fast-growing need for expertise in Geographic Information Systems (GIS), Geographic Information Science
-
, or probabilistic modeling, and be proficient in Python and modern machine-learning frameworks (ideally PyTorch). Experience with single-cell transcriptomics, epigenomics, proteomics, spatial omics, or multimodal
-
. Continuous observations, carried out over long periods, are at the heart of the research conducted at ISTerre. They are essential for understanding, modeling, and anticipating the natural processes visible
-
particular, the research project will focus on inferring trajectories from spatial transcriptomics data modelling at the same time the cells evolution in gene expression and in space. Required skills : We
-
will develop novel machine learning and artificial intelligence (ML/AI) methods for genomics data, especially: large-scale single-cell genomics data, high-definition spatial genomics, digital pathology
-
Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Oldenburg Oldenburg, Niedersachsen | Germany | 5 days ago
CCAMLR meeting: the expiration of Conservation Measure (CM) 51-07, which previously mandated that the maximum allowable catch of 620.000 t be spatially distributed among subareas 48.1 to 48.4. With