Sort by
Refine Your Search
-
Listed
-
Country
-
Field
-
of conflict prediction. Lead the design and improvement of ensemble routines and validation protocols in the VIEWS forecasting system. Publish research findings in top peer-reviewed journals and contribute
-
surrogates of electronic Hamiltonians. The postdoctoral researcher will develop graph neural networks based on the MACE architecture to predict Hamiltonian elements for 2D materials and van der Waals
-
Learning for Predicting Future Danish Land Use under Compound Climate Impacts, funded by the Villum Foundation (Synergy Programme). Two postdoctoral researchers will collaborate across AAU’s Departments
-
University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
prediction using large-scale multimodal neuroimaging data. The research will emphasize methodological innovation in statistical modeling, transfer learning, machine learning, model ensemble strategies, and
-
of Aalborg University. Job Description This position is part of the cross-disciplinary DK-Future project – Probabilistic Geospatial Machine Learning for Predicting Future Danish Land Use under Compound Climate
-
at Linköping University, where we laid the foundation for recent breakthroughs in protein structure prediction, which was later awarded the 2024 Nobel Prize in Chemistry. Since then, we have further developed
-
of electronic Hamiltonians. The postdoctoral researcher will develop graph neural networks based on the MACE architecture to predict Hamiltonian elements for 2D materials and van der Waals heterostructures, with
-
combined with modeling experiments or enhanced research in parameterization, AI is accelerating computational processes, improving prediction accuracy, and enabling the creation of extensive model ensembles