Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- Technical University of Denmark
- Utrecht University
- ETH Zurich
- ;
- ; University of Exeter
- ; University of Sheffield
- DAAD
- Delft University of Technology (TU Delft)
- Maastricht University (UM)
- RMIT University
- Radboud University
- University of Cambridge
- University of Groningen
- ; Max Planck Institute for Psycholinguistics
- ; Swansea University
- ; University of Southampton
- ; University of Sussex
- ; University of Warwick
- Aston University
- CNRS
- Chalmers University of Technology
- ETH Zürich
- Inria, the French national research institute for the digital sciences
- Institut Pasteur
- Karolinska Institutet
- Ludwig-Maximilians-Universität München •
- Nature Careers
- Sveriges lantbruksuniversitet
- Swedish University of Agricultural Sciences
- Tampere University
- Technical University Of Denmark
- Technical University of Munich
- Tilburg University
- University of Basel
- University of Luxembourg
- University of Newcastle
- University of Oslo
- 27 more »
- « less
-
Field
-
) for engineering systems. Our research covers surrogate modeling, reliability analysis, sensitivity analysis, optimization under uncertainty, and Bayesian calibration. We are known for developing the UQLab software
-
addressing specific case studies or specific targeted techniques. The main tools to be used will come from the discipline of Machine Learning, particularly those based on Bayesian methods. The student will be
-
. The BayesCompare project is a FNR funded project on Bayesian comparisons between artificial and natural representations to improve our understanding how natural and artificial intelligences process information
-
systems (CDSSs), so that their use in the clinic can be subject to rigorous quality control and certification. In this position, you will work on exploring synergies between Bayesian networks and AutoML
-
these relate to societal and individual-level challenges. The BayesCompare project is a FNR funded project on Bayesian comparisons between artificial and natural representations to improve our understanding how
-
for individuals living with multiple long-term conditions known as multimorbidity, and may lead to unnecessary polypharmacy. This PhD studentship aims to develop a Bayesian modelling framework to identify clusters
-
modern Bayesian modelling frameworks such as Stan, Turing.jl, and PyMC, including automatic differentiation frameworks, MCMC sampling algorithms, and iterative Bayesian modelling. Special attention will be
-
behaviour using computational approaches such as Bayesian program synthesis and inverse reinforcement learning. Investigate the diversity of motor commands that could implement observed behaviours and explore
-
) for engineering systems. Our research covers surrogate modeling, reliability analysis, sensitivity analysis, optimization under uncertainty, and Bayesian calibration. We are known for developing the UQLab software
-
cutting edge Bayesian methods to design and analyse studies in diagnostics, with a focus on adaptive and seamless designs in diagnostic test development. The position has a fixed duration of 18 months