Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- MOHAMMED VI POLYTECHNIC UNIVERSITY
- Harvard University
- University of Oxford
- Delft University of Technology (TU Delft)
- National Aeronautics and Space Administration (NASA)
- Texas A&M University
- University of Groningen
- Utrecht University
- Aalborg University
- Argonne
- Boise State University
- CNRS
- Cornell University
- EPFL
- Erasmus University Rotterdam
- Inria, the French national research institute for the digital sciences
- Institutionen för biologi och miljövetenskap
- Instituto Superior Técnico
- KTH Royal Institute of Technology
- King Abdullah University of Science and Technology
- Lancaster University
- Lehigh University
- Northeastern University
- Oak Ridge National Laboratory
- Pennsylvania State University
- Rutgers University
- St Jude Children's Research Hospital
- Stanford University
- Stony Brook University
- Technical University of Munich
- University College Dublin
- University of California
- University of Cambridge;
- University of Liverpool
- University of Miami
- University of Minnesota
- University of New Hampshire
- University of North Carolina at Chapel Hill
- University of Potsdam
- University of Twente
- University of Twente (UT)
- University of Washington
- Washington State University
- 33 more »
- « less
-
Field
-
forecasting and predictive modelling Biodiversity change in human-modified landscapes The specific research focus is open to development together with the successful candidate, and may connect with ongoing work
-
The past decades have been associated with substantial losses of sea ice over both hemispheres. Existing climate models are currently unable to accurately forecast these changes, in part due
-
help reduce uncertainties in climate forecasts and better assess the effects of aerosols on atmospheric systems. The postdoctoral researcher's mission will be to develop and improve the WRF-Chem model
-
sensitivity of 4D-Var performance to assimilation windows, error models, boundary conditions, and observational coverage. Integrate model estimates and forecasts with observations from oceanographic sensors and
-
associated with substantial losses of sea ice over both hemispheres. Existing climate models are currently unable to accurately forecast these changes, in part due to their imperfect representation of ocean
-
), ISCTE. Organic Unit: Centre for Computational and Stochastic Mathematics Scholarship Theme: A Forecasting Framework for Pandemic Monitoring and Decision-Making Duration: 6 months Maximum Duration
-
detection, forecasting, process monitoring, and control; integrating multimodal data from imaging, spectroscopy, IoT sensors, remote sensing, environmental measurements, and process systems; developing robust
-
and associated environmental impacts. Contribute to short-term (2026 to 2030) and long-term (2030 to 2050) verticalisation forecasting models based on machine learning, and to their validation against
-
is preferred. Experience with regional ocean model configuration, operational ocean forecasting, data assimilation, model downscaling, or coupled ocean-atmosphere-wave modeling is desirable
-
. By building on recent developments and requirements for uncertainty quantification in volcanic ash forecasting you will develop computationally efficient techniques that maintain the speed required