Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- NTNU - Norwegian University of Science and Technology
- ;
- Utrecht University
- Cranfield University
- ; University of Warwick
- Ghent University
- Humboldt-Stiftung Foundation
- Molde University College
- Technical University of Munich
- University of Twente
- ; University of Sheffield
- Monash University
- ; University of Nottingham
- Aalborg University
- Chalmers University of Technology
- DAAD
- RMIT University
- Radboud University
- Technical University of Denmark
- University of Bergen
- University of Nottingham
- Wageningen University and Research Center
- ; Newcastle University
- ; Swansea University
- ; The University of Manchester
- ; University of Birmingham
- ; University of Liverpool
- ; University of Southampton
- Aarhus University
- CWI
- Copenhagen Business School , CBS
- ETH Zurich
- Forschungszentrum Jülich
- Harper Adams University
- Leiden University
- Ludwig-Maximilians-Universität München •
- Norwegian University of Life Sciences (NMBU)
- University of Adelaide
- University of Münster •
- University of Oxford
- 30 more »
- « less
-
Field
-
techniques like generalisations of Autoregressive Integrated Moving Average (ARIMA) models, Dynamic Linear Models (DLM) and joint longitudinal and survival models. To appropriately capture uncertainty
-
and data analytics (including machine learning and deep learning); from high-performance computing to high-performance analytics; from data integration to data-related topics such as uncertainty
-
-leading climate experts with the aim to address existing uncertainties about climate feedbacks at the boundaries between oceans, land, ice, and atmosphere. Our interdisciplinary approach and state
-
of investigation, many predictive tools lack robust ways to incorporate uncertainties in boundary conditions, turbulence modelling, and manufacturing variability. Problem Statement Conventional CFD workflows assume
-
integrates machine learning and statistics to improve the efficiency and scalability of statistical algorithms. The project will develop innovative techniques to accelerate computational methods in uncertainty
-
. This announcement text is a translation from the Norwegian announcement text. If there is doubt about the interpretation of the English announcement text, the Norwegian version prevails. Questions about the position
-
can nonetheless not be guaranteed. This announcement text is a translation from the Norwegian announcement text. If there is doubt about the interpretation of the English announcement text
-
-year research programme, funded by NWO(link is external) , EMBRACER brings together a wide range of world-leading climate experts with the aim to address existing uncertainties about climate
-
feasibility studies (like CO2 footprint) Assessment of the results, including evaluation of simplifications and uncertainties and their impact on the results. Present the work that has been performed and its
-
to investigate the cognitive and social behaviour (such as knowledge acquisition, organization, and transmission, recognition processes, or risk assessment and decision-making under uncertainty) involved in