Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- Nature Careers
- Argonne
- Indiana University
- Emory University
- King Abdullah University of Science and Technology
- McGill University
- Technical University of Denmark
- Tilburg University
- University of Liverpool
- University of Minnesota
- University of Oslo
- University of Oxford
- Czech Technical University in Prague
- Dartmouth College
- Duke University
- Ghent University
- ICN2
- Inria, the French national research institute for the digital sciences
- Institut de Físiques d'Altes Energies (IFAE)
- Lehigh University
- Lunds universitet
- Massachusetts Institute of Technology
- Max Planck Institute for Multidisciplinary Sciences, Göttingen
- National Aeronautics and Space Administration (NASA)
- National Centre for Nuclear Research
- North Carolina State University
- Oak Ridge National Laboratory
- Rice University
- Rutgers University
- Singapore-MIT Alliance for Research and Technology
- The Ohio State University
- The Peace Research Institute Oslo (PRIO)
- The University of South Dakota
- Umeå University
- Umeå universitet
- University of Cambridge;
- University of Idaho
- University of Liverpool;
- University of Miami
- University of Split, Faculty of civil engineering, architecture and geodesy
- University of Tübingen
- University of Washington
- Utrecht University
- Wageningen University & Research
- 34 more »
- « less
-
Field
-
quantitative and analytic skills. Preferred Qualifications Experience with evidence-accumulation models (DDM, sequential sampling, Bayesian models). Experience with computer vision tools (e.g., MediaPipe
-
University of Split, Faculty of civil engineering, architecture and geodesy | Croatia | 3 months ago
in karst using hierarchical Bayesian physical neural networks'' for a fixed period of time (maximum two years) for the duration of the project at the SARLU or Hydrotechnical Engineering. Where to apply
-
research with young children Experience with computational methods (e.g., Bayesian modeling, drift diffusion modeling, etc.) Equipment Utilized Physical Demands and Work Environment Overview Statement
-
for estimating soil organic matter dynamics. Demonstrated experience in applying Bayesian statistical approaches to soil science questions. Knowledge in soils and soil management issues of Ohio and the greater
-
by combining all available data, taking advantage of the varying temporal resolution and different time spans that the records cover. This work will involve Bayesian tools developed by our research
-
statistical methods such as dimensionality reduction and Bayesian modeling. This project offers access to a rich, curated clinical dataset and collaboration with leading neurologists, neurosurgeons, and data
-
through to large-scale individual-based simulation as well as statistics and Bayesian inference. This highly motivated, collaborative research group leads funded, international consortia in modelling, NTDs
-
qualifications: • Strong background in modelling, including spatial and temporal/dynamic modelling, demographic modelling, Bayesian hierarchical models and/or modelling with multiple data streams
-
, particularly radionuclides, on a continental scale. The aim is to develop a new class of inverse Bayesian models, STE-EU-SCALE, combining innovative forward dispersion models, machine learning techniques, and
-
, Statistics, or related fields No experience required Skills: Strong expertise in the theory and application of birth-death and related stochastic processes Proficiency in both frequentist and Bayesian