Sort by
Refine Your Search
-
Listed
-
Country
-
Program
-
Employer
- Chalmers University of Technology
- University of Oslo
- Cornell University
- Curtin University
- Duke University
- Harvard University
- Indiana University
- Inria, the French national research institute for the digital sciences
- RIKEN
- Rice University
- Swansea University
- Technical University of Denmark
- UCL;
- UNIVERSITY OF SOUTHAMPTON
- Umeå universitet
- University of Birmingham
- University of Connecticut
- University of Minnesota
- University of Nottingham
- 9 more »
- « less
-
Field
-
entitled “Beyond Data-Augmentation: Advancing Bayesian Inference for Stochastic Disease Transmission Models”. The overarching aim of the project is to develop the next generation of statistical tools
-
relevant to modern data science (e.g., Bayesian or frequentist inference, information theory, uncertainty quantification, high-dimensional methods). Programming skills in Python and/or R, with evidence of
-
expertise in areas such as approximate inference, Bayesian statistics, continuous optimization, information geometry, etc. We work on a variety of learning problems, especially those involving supervised
-
field (e.g., geography, resource management, environmental studies/science, or related disciplines) with strong experience in causal inference research. The ideal candidate will be a highly motivated
-
experience in one or more of: large-scale data analysis, time-series photometry, spectroscopy, astrometry, Bayesian/statistical inference, and/or software development for astronomical datasets. Department
-
. The postholder will be based in the Center for Communicable Disease Dynamics within the Department of Epidemiology, and will be a member of the HIV Inference Group a geographically distributed and substantively
-
2028 working 21 hours per week. We are looking for a Senior Research Fellow in Statistics to advance the dynamic research portfolio of the Population Data Science group (https://popdatasci.swan.ac.uk
-
/bayesian/deep-learning analyses, with functional validation in spruce via CRISPR-Cas9 and nanoparticle delivery. The postdoc will join Professor Nathaniel R. Street’s team at UPSC, working closely with
-
, Artificial Intelligence , Bayesian Statistics , Big Data , Scientific Machine Learning , Social Sciences , Biomedical Informatics , Causal Inference , Computational Social Science , Data Science and
-
getting Bayesian type uncertainty for parameters given data (i.e., a posterior type distribution over the parameter space) without specifying a model nor a prior. Such methods can in principle be applied