Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Field
-
study examining common elements in decisions across different contexts (risk, uncertainty, time; gains, losses, and mixed domain choices). Applying Bayesian techniques to develop stochastic models
-
generation of health data scientists. Areas of expertise include bioinformatics, computational biology, artificial intelligence, network science, Bayesian methods, spatiotemporal methods, visualization
-
in chemistry and biology, approaches for extracting relevant information from foundation models, and/or methods for adaptive experimental design such as active learning or Bayesian optimization
-
. quantitative and/or qualitative counterfactual-based approaches, Difference in Difference models, Qualitative Comparative Analysis, Bayesian hierarchical modelling); o Experience working with and synthesizing
-
impact-based health early warning systems. The successful candidate will join the research team of Dr. Joan Ballester Claramunt (https://www.joanballester.eu/ ) at ISGlobal within the framework
-
Agencies will be returned. Prior to application, further information (including application procedure) should be obtained from the Work at UCD website: https://www.ucd.ie/workatucd/jobs/ Where to apply
-
of Biostatistics and Population Health (BPH, https://medicine.osu.edu/departments/biomedical-informatics/divisions/division-of-biostatistics-and-population-health ) in the Department of Biomedical Informatics (BMI
-
development, testing and application of the LPJ-GUESS biosphere model for modelling tropical wetlands and estimating tropical methane emissions. The work is part of the EU-funded project IM4CA (https://im4ca.eu
-
work is the Department of Biostatistics (OCBE), Domus Medica, Gaustad UiO campus, Oslo. Job description The position is connected to the project “Bayesian Enhanced Tensor Factorization Embedding
-
Elhoseiny, Code: https://github.com/yli1/CLCL Uncertainty-guided Continual Learning with Bayesian Neural Networks (ICLR’20), Sayna Ebrahimi, Mohamed Elhoseiny, Trevor Darrell, Marcus Rohrbach, Code: https