Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- University of Oslo
- Linköping University
- NTNU - Norwegian University of Science and Technology
- Aalborg University
- Monash University
- NTNU Norwegian University of Science and Technology
- Technical University of Munich
- Nature Careers
- Technical University of Denmark
- Uppsala universitet
- Utrecht University
- CNRS
- Eindhoven University of Technology (TU/e)
- Newcastle University
- Umeå University
- Vrije Universiteit Brussel (VUB)
- Ariel University
- IMDEA Networks Institute
- Medical University of Innsbruck
- Northeastern University London
- Purdue University
- SciLifeLab
- The University of Manchester
- University of Amsterdam (UvA)
- University of Exeter
- University of Plymouth
- University of Sheffield
- University of Southern Denmark
- Wageningen University & Research
- 3rdplace
- ;
- Aalborg Universitet
- Aarhus University
- BRGM
- Biology Centre CAS
- COPENHAGEN BUSINESS SCHOOL
- Centrale Supelec
- Chalmers University of Technology
- Constructor University Bremen gGmbH
- Copenhagen Business School
- Coventry University Group
- Delft University of Technology (TU Delft)
- ETH Zürich
- Ecole Centrale de Lyon
- Ecole Centrale de Nantes
- Electronics and Informatics Department
- Erasmus University Rotterdam
- Forschungszentrum Jülich
- Fraunhofer-Gesellschaft
- French National Research Institute for Agriculture, Food and Environment (INRAE)
- GFZ Helmholtz-Zentrum für Geoforschung
- Grenoble INP - Institute of Engineering
- HBIGS Heidelberg Biosciences International Graduate School
- Heidelberg University
- Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt
- Helmholtz-Zentrum Hereon
- INRIA
- IT4Innovations National Supercomputing Center, VSB - Technical University of Ostrava
- Inria, the French national research institute for the digital sciences
- Institut de Recherche pour le Développement (IRD)
- Instituto Superior de Agronomia
- Integreat -Norwegian Centre for Knowledge-driven Machine Learning
- King's College London
- King's College London;
- Leibniz
- Ludwig-Maximilians-Universität München •
- Luleå tekniska universitet
- Maastricht University (UM)
- Nicolaus Copernicus Astronomical Center
- Swedish University of Agricultural Sciences
- The University of Iowa
- Trinity College Dublin
- UCL
- UNamur - Lab of F. De Laender
- Umeå universitet
- Universite de Montpellier
- University of Basel
- University of Bologna
- University of East Anglia
- University of East Anglia;
- University of Essex;
- University of Exeter;
- University of Luxembourg
- University of Newcastle
- University of Oxford
- University of Surrey
- University of Texas at El Paso
- Université Paris Cité
- Université de Caen Normandie
- Université de Liège
- Vrije Universiteit Brussel
- 81 more »
- « less
-
Field
-
modelling, data assimilation, and multi-scale neural network architectures applied to spatio-temporal data. The development of these methods is motivated by a concrete and important application: inferring gas
-
stimulated luminescence (OSL) dating of sediments and rocks, palaeoseismology, megaliths, Bayesian chronological modelling, archaeoseismicity, stable continental regions (SCR), Armorican Massif. Context and
-
in English Candidates without a master’s degree have until 01.09.2026 to complete the final exam. Desired qualifications: Solid foundation in Bayesian statistics, empirical Bayes methods and advanced
-
-informed / simulation-aware modeling Efficient algorithms for design-space exploration (e.g., surrogate modeling, Bayesian optimization, differentiable programming) Hybrid approaches combining data-driven
-
motivated candidate with a strong background in statistics and/or machine learning. Areas of particular interest include, but are not limited to: Causal Discovery and Causal Inference Extreme Value Theory
-
of such models should then be demonstrated by informing training and inference processes. A range of different strategies can be explored, including new ways to derive model distributions and model parameter
-
, the PhD student at ETRO will contribute to the core of the AI pipeline by designing and validating generative models (e.g. latent diffusion-, autoencoder-, and GAN-based approaches) that can infer
-
methods a broad range of statistical inference tasks in quantum systems with applications to quantum sensing, computing and communications. Topics will include: Sequential and universal inference: adaptive
-
medical applications. Federated Bayesian learning offers a solution to those problems by allowing multiple participants to train machine learning models collaboratively, without sharing any data. Bayesian
-
transformations. The project investigates a hybrid approach that combines deep learning with grammatical inference to develop models that are interpretable, efficient, and mathematically verifiable while leveraging