Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- Nature Careers
- Argonne
- NEW YORK UNIVERSITY ABU DHABI
- Technical University of Munich
- ;
- Cornell University
- European Space Agency
- Stony Brook University
- Technical University of Denmark
- University of Oxford
- Heriot Watt University
- King Abdullah University of Science and Technology
- Leibniz
- MOHAMMED VI POLYTECHNIC UNIVERSITY
- Stanford University
- Texas A&M University
- Umeå University
- Utrecht University
- Aalborg University
- Brookhaven Lab
- CEA
- CWI
- Chalmers University of Technology
- Florida International University
- Ghent University
- Imperial College London
- KINGS 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
- NORCE
- National Aeronautics and Space Administration (NASA)
- National Renewable Energy Laboratory NREL
- Northeastern University
- Nottingham Trent University
- Pennsylvania State University
- Rutgers University
- The Ohio State University
- The University of Arizona
- UNIVERSITY OF HELSINKI
- University College Cork
- University of California Berkeley
- University of Delaware
- University of Hull
- University of Miami
- University of Southern California
- University of Southern Denmark
- University of Tübingen
- University of Virginia
- WIAS Berlin
- 42 more »
- « less
-
Field
-
• Uncertainty quantification around LLMs • Constrained optimal experimental design (active learning) • Combining models and combining data / Realistic simulation of clinical trials • Developing
-
other sources to train and validate AI models. Develop computational workflows incorporating LLMs, Monte Carlo Tree Search (MCTS), phylogenetic inference, uncertainty quantification, and epidemiological
-
), Proficiency with LCA software tools (e.g., openLCA, SimaPro, Brightway, Activity Browser), Experience with LCA uncertainty, sensitivity analysis, and scenario modelling, Energy systems modelling and simulation
-
to increasing CO2 and climatic change is a large uncertainty for ecosystems, crop productivity and climate predictions. To tackle this uncertainty, we combine: growth chamber experiments, samples from world
-
plants will respond to increasing CO2 and climatic change is a large uncertainty for ecosystems, crop productivity and climate predictions. To tackle this uncertainty, we combine: growth chamber
-
of biological hedging shape conservation strategies? Can financial tools like biodiversity bonds or species-indexed futures promote better ecological outcomes? How should we account for uncertainty in
-
uncertainties and result errors throughout the whole data assimilation and modeling process. ● Other Duties as assigned. Special Notes: The Research Foundation of SUNY is a private educational corporation
-
uncertainties and result errors throughout the whole data assimilation and modeling process. ● Other Duties as assigned. Special Notes: The Research Foundation of SUNY is a private educational corporation
-
, global geopolitical dynamics and uncertainties in the supply of critical materials threaten energy system resilience. This transition relies on advanced technologies and renewable fuels. Therefore, unlike
-
a testbed of micromorphic numerical models, and metamaterials. Proposing experimental methods to obtain micromorphic models under small and large strain, with coupled uncertainty quantification