Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- Nature Careers
- ;
- University of Groningen
- Cranfield University
- Technical University of Denmark
- DAAD
- RMIT University
- Technical University of Munich
- University of Cambridge
- Curtin University
- Monash University
- Purdue University
- University of British Columbia
- University of Twente
- Wageningen University and Research Center
- Georgetown University
- SciLifeLab
- ; University of Warwick
- Chalmers University of Technology
- Erasmus University Rotterdam
- Leibniz
- University of Tübingen
- ; Swansea University
- Leiden University
- NTNU - Norwegian University of Science and Technology
- Queensland University of Technology
- University of Adelaide
- University of Luxembourg
- University of Oslo
- ; University of Exeter
- Ghent University
- Institut Pasteur
- Ludwig-Maximilians-Universität München •
- THE UNIVERSITY OF HONG KONG
- Temple University
- The University of Iowa
- University of Copenhagen
- University of Newcastle
- ; Durham University
- ; Edge Hill University
- ; University of Birmingham
- ; University of Bristol
- ; University of Surrey
- Aalborg University
- CWI
- Duke University
- Forschungszentrum Jülich
- Friedrich Schiller University Jena •
- Goethe University Frankfurt •
- KNAW
- Susquehanna International Group
- The Ohio State University
- Umeå University
- Universidad Nacional Autónoma de México
- University of Bergen
- University of Göttingen •
- University of Konstanz •
- University of Minnesota
- University of Nebraska–Lincoln
- University of Nottingham
- University of Oregon
- University of Pittsburgh
- University of Southern Denmark
- VIB
- ; Bournemouth University
- ; Brunel University London
- ; EPSRC Centre for Doctoral Training in Green Industrial Futures
- ; Loughborough University
- ; Max Planck Institute for Psycholinguistics
- ; Midlands Graduate School Doctoral Training Partnership
- ; Newcastle University
- ; The University of Manchester
- ; UCL
- ; University of Greenwich
- ; University of Oxford
- ; University of Reading
- ; University of Southampton
- ; University of Sussex
- Aarhus University
- Ariel University
- Arizona State University
- CISPA (at University of Stuttgart)
- East Carolina University
- Fermilab
- Fred Hutchinson Cancer Center
- Freie Universität Berlin •
- Heidelberg University
- Helmholtz-Zentrum Geesthacht
- Humboldt-Universität zu Berlin •
- Imperial College London
- Indiana University
- Lincoln University
- MOHAMMED VI POLYTECHNIC UNIVERSITY
- MPINB
- Max Planck Institute for Infection Biology •
- Max Planck Institute for Mathematics •
- Max Planck Institute for Molecular Genetics •
- Max Planck Institute for Neurobiology of Behavior - caesar, Bonn
- Max Planck Institute for Plant Breeding Research, Köln
- Max Planck Institute for Social Law and Social Policy, München
- 90 more »
- « less
-
Field
- Computer Science
- Medical Sciences
- Biology
- Economics
- Engineering
- Mathematics
- Materials Science
- Linguistics
- Science
- Psychology
- Chemistry
- Environment
- Arts and Literature
- Humanities
- Electrical Engineering
- Social Sciences
- Business
- Earth Sciences
- Education
- Law
- Sports and Recreation
- Physics
- Statistics
- 13 more »
- « less
-
optimization of batteries against the swelling phenomenon. This project aims at developing scientific machine learning approaches based on the Bayesian paradigm and electrochemical-thermomechanical models in
-
Bayesian inference framework for identifying complex aerospace systems combining with limited experimental data. It can be also used to quantify uncertainties from experimental testing, significantly
-
derived use cases by focusing on one or more of the following topics in their PhD project: Training and inference of ML models on GPU clusters. Method development for scalable and green AI. Use cases in
-
methods for causal inference in observational data, is strongly preferred. Using various existing large datasets with rich information for knowledge synthetisation and triangulation over the course of the
-
challenging, and new theoretical methods and algorithms are required. The research project aims at deriving priors for Bayesian methods from atomistic simulations and machine learning. It also offers
-
for clinical use. Generative and Predictive AI for Clinical Decision Support and Statistical Inference Develop biologically informed statistical methods and uncertainty estimation models to train deep learning
-
. mixed effects regression models and/or Bayesian statistics). You have experience in conducting empirical research (e.g., experimental design, stimuli selection, recruitment, participant testing, report
-
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
-
-mechanical phase-field model incorporating hydrogen diffusion, mechanical degradation, and fracture evolution. - Employ physics-informed neural networks (PINNs) to infer hidden fields and accelerate
-
to the requirements for learning or inference by various AI modules deployed in the devices and the network. This line of work will investigate the fundamental tradeoffs among latency, accuracy, and energy efficiency