Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- Nature Careers
- Argonne
- NEW YORK UNIVERSITY ABU DHABI
- ;
- KINGS COLLEGE LONDON
- MOHAMMED VI POLYTECHNIC UNIVERSITY
- Stony Brook University
- Cornell University
- Heriot Watt University
- INESC ID
- King Abdullah University of Science and Technology
- Leibniz
- National Aeronautics and Space Administration (NASA)
- Stanford University
- Technical University of Denmark
- Technical University of Munich
- Umeå University
- University of Oxford
- Utrecht University
- Aarhus University
- Brookhaven Lab
- CEA
- CNRS
- CWI
- Chalmers University of Technology
- Duke University
- Eindhoven University of Technology (TU/e)
- Eindhoven University of Technology (TU/e); Eindhoven
- European Space Agency
- Florida International University
- Georgia Institute of Technology
- IFP Energies nouvelles (IFPEN)
- Imperial College London
- King's College London
- Los Alamos National Laboratory
- Manchester Metropolitan University
- Massachusetts Institute of Technology (MIT)
- Max Planck Institute for Dynamics and Self-Organization, Göttingen
- McGill University
- Michigan Technological University
- NORCE
- National Renewable Energy Laboratory NREL
- North Carolina State University
- Northeastern University
- Nottingham Trent University
- Oak Ridge National Laboratory
- Pennsylvania State University
- SUNY University at Buffalo
- Texas A&M AgriLife
- The Ohio State University
- The University of Arizona
- UNIVERSITY OF HELSINKI
- University at Buffalo
- University of Florida
- University of Hull
- University of Miami
- University of Southern California
- University of Southern Denmark
- University of Sydney
- University of Texas at Austin
- University of Virginia
- Université Savoie Mont Blanc
- WIAS Berlin
- 53 more »
- « less
-
Field
-
, · quantifying uncertainty in causal links, · integrating the resulting models into neural networks (or other machine learning models) to detect and predict anomalies or anticipate failures. The research
-
-based crop modeling, uncertainty characterization, digital agronomy, remote sensing Additional qualifications Further, we will prefer candidates with some of the following qualifications: Teaching and
-
-based crop modeling, uncertainty characterization, digital agronomy, remote sensing Additional qualifications Further, we will prefer candidates with some of the following qualifications: Teaching and
-
) information-theoretic active learning, and c) capturing uncertainty in deep learning models (including large language models). The successful postholder will hold or be close to the completion of a PhD/DPhil in
-
with health surveillance and related data to estimate climate-attributable risk under Deep Uncertainty. The candidate will also contribute to the development of interactive tools and training materials
-
modelling with remote sensing data, novel approaches to uncertainty quantification, especially as applied to environmental problems. In The University of Sydney’s Faculty of Engineering, you’ll join a group
-
models; 2. Statistical methods, analysis, and inference for large-scale computational simulator applications; 3. Uncertainty representation, quantification and propagation; and 4. Scalable data science
-
from telescope data. The design of robust uncertainty quantification tools is a core component of this effort. -On the experiment design side, the group develops simulation and optimization algorithms
-
to evaluate to what extent ongoing scientific discrepancies and uncertainties are a consequence of (i) people using different methodological approaches, (ii) the types of data considered (including possible
-
motivated researcher with a strong background in computational modeling, system identification, and uncertainty quantification for civil infrastructure. The successful candidate will join the Risk Assessment