Sort by
Refine Your Search
-
Listed
-
Country
-
Employer
- Monash University
- University of Sheffield
- ;
- ETH Zurich
- University of Glasgow
- Forschungszentrum Jülich
- NIST
- Nature Careers
- Northeastern University
- University of Lund
- University of Toronto
- Yale University
- Columbia University
- Duke University
- Fraunhofer-Gesellschaft
- Rice University
- SUNY Polytechnic Institute
- SciLifeLab
- Stony Brook University
- University of Bristol
- University of Cambridge
- University of Houston Central Campus
- Aalborg University
- Aston University
- BNU-HKBU United International College
- Baylor College of Medicine
- CEA
- Career Education Corporation
- Case Western Reserve University
- Colorado Technical University
- Erasmus University Rotterdam
- Freenome
- Harbin Engineering University
- Harvard University
- Heriot Watt University
- Imperial College London
- Institut Pasteur
- KINGS COLLEGE LONDON
- Leibniz
- Michigan State University
- Nanyang Technological University
- Oak Ridge National Laboratory
- Queensland University of Technology
- RMIT University
- SUNY University at Buffalo
- Simons Foundation/Flatiron Institute
- Technical University of Munich
- The University of Chicago
- University of Alabama, Tuscaloosa
- University of California, Los Angeles
- University of Delaware
- University of Florida
- University of Hong Kong
- University of Nebraska–Lincoln
- University of North Carolina Wilmington
- University of North Carolina at Chapel Hill
- University of Nottingham
- University of Oregon
- University of Oslo
- University of Texas Health Science Center San Antonio
- University of Texas at Arlington
- University of Utah
- University of Warsaw
- University of Washington
- Zintellect
- 55 more »
- « less
-
Field
-
structures, Bayesian approaches are proposed along with the supersaturated and D-optimal designs in the literature. This project aims to explore the current literature on Bayesian supersaturated D-optimal
-
The relationship between the information-theoretic Bayesian minimum message length (MML) principle and the notion of Solomonoff-Kolmogorov complexity from algorithmic information theory (Wallace and
-
increasingly important, but also more complex, due to rising demands on performance, precision, quality, and sustainability. Bayesian optimization (BO) - a special machine learning approach - represents a
-
Bayesian system identification in nonlinear engineering dynamics School of Mechanical, Aerospace and Civil Engineering PhD Research Project Directly Funded Students Worldwide Prof Keith Worden
-
clinical trials to assess its ability to measure hydration state. This project would use data from WearOptimo’s hydration sensor and develop novel Bayesian methods to model hydration state. How can hydration
-
plants they visit and pollinate. Bayesian networks (BNs), and other probabilistic graphical models, can provide a visual representation of the underlying structure of a complex system by representing
-
Sequential Monte Carlo Methods for Bayesian Inference in Complex Systems School of Electrical and Electronic Engineering PhD Research Project Self Funded Prof Lyudmila Mihaylova Application Deadline
-
This PhD project is funded by a successful ARC Discovery Project grant: "Improving human reasoning with causal Bayesian networks: a user-centric, multimodal, interactive approach" and the successful
-
exploration strategies that go beyond traditional techniques such as linear programming or deterministic solvers. You will work on cutting-edge methods including: Bayesian optimization Surrogate modeling
-
Bayesian system identification in nonlinear engineering dynamics