Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Employer
- University of Cambridge;
- University of Glasgow
- SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
- University of Sheffield
- Imperial College London
- King's College London
- Lancaster University
- The University of Manchester
- University of Birmingham
- University of Cambridge
- University of Liverpool
- University of Liverpool;
- AALTO UNIVERSITY
- Abertay University
- Earlham Institute
- Iliad
- Imperial College London;
- The University of Edinburgh;
- The University of Manchester;
- UNIVERSITY OF MELBOURNE
- University of Bristol
- University of Exeter
- University of London
- University of Manchester
- University of Oxford
- University of Sheffield;
- University of Surrey
- University of Warwick;
- 18 more »
- « less
-
Field
-
the best outcome. Precision medicine methods leverage individual-level characteristics to help optimise treatment choices for individuals. This project will leverage recent advances in Bayesian statistical
-
uncertainty about those conclusions (uncertainty quantification). Bayesian inference and experimental design methods are increasingly used in scientific practice, and offer appealing theoretical guarantees when
-
before the deadline. In many applications such as biological sciences, social science, and engineering, we encounter high-dimensional observations. Bayesian approach can provide a flexible modeling
-
Approximation calculations, whose direct use in Bayesian parameter estimation is currently computationally prohibitive. By providing a fast and statistically controlled surrogate for these calculations
-
attribution studies, including analyses during heatwaves. The role involves using and developing methods such as case-crossover designs, distributed lag non-linear models, Bayesian hierarchical models
-
Haslinger and Professor Jason Ralph. The team brings together Liverpool’s strengths in wave propagation and scattering in complex media, mathematical modelling, Bayesian inference and information fusion
-
dinosaurs, squamates, and amphibians). They will use Bayesian statistics to test for trends in brain size change over time and phylogeny, test for correlations between brain size and neuron counts in extant
-
. The team brings together Liverpool’s strengths in wave propagation and scattering in complex media, mathematical modelling, Bayesian inference and information fusion, signal processing, tracking and the
-
research environment and/or a record of publication in relevant, refereed journals. Experience with epidemiological data designs, such as cohort and case-crossover studies. Experience with Bayesian
-
and may come from any relevant area of theoretical or computational physics, including gravitation, field theory, lattice and numerical field theory, cosmological perturbation theory, Bayesian