Sort by
Refine Your Search
-
Listed
-
Employer
- Nature Careers
- Leibniz
- Forschungszentrum Jülich
- Fraunhofer-Gesellschaft
- University of Tübingen
- Technische Universität München
- Heidelberg University
- Technical University of Munich
- University of Bonn
- ;
- DAAD
- GSI Helmholtzzentrum für Schwerionenforschung
- Free University of Berlin
- Karlsruher Institut für Technologie (KIT)
- LUDWIG MAXIMILIANS UNIVERSITAET MUENCHEN
- Max Planck Institute for Brain Research, Frankfurt am Main
- Max Planck Institute for Mathematics
- Max Planck Institute for Plant Breeding Research, Cologne
- Max Planck Institute for Social Anthropology, Halle (Saale)
- Max Planck Institute of Molecular Cell Biology and Genetics
- Max Planck Institute of Molecular Cell Biology and Genetics, Dresden
- RWTH Aachen University
- University of Münster
- University of Tuebingen
- 14 more »
- « less
-
Field
-
, complex dynamical systems analysis, efficient generative learning methods for statistical mechanics, highly accurate machine learning methods for quantum mechanics and inference and enhancement of cutting
-
learning models Implementation of deep learning Improvement of models, e.g. in terms of efficiency, training performance or inference behavior What you bring to the table Enrolled Bachelor's/Master's student
-
, as part of the development, one position located in Görlitz as Research Associate / PhD student (f/m/x) Integration of CMOS detector technology into the Universal Bayesian Imaging Kit (UBIK) (subject
-
be inferred from models that are incomplete and data that involve errors. For such challenges, Bayesian analysis using Markov Chain Monte Carlo (MCMC) has become the gold standard. For addressing high
-
at Forschungszentrum Jülich. Together with local research institutes, you will develop and utilize methods of scalable training and inference towards stronger generalization and transfer with the aim to address a
-
of efficiency, training performance or inference behavior What you bring to the table Enrolled Bachelor's/Master's student in full-time studies in the fields of computer science, mathematics, physics, electrical
-
and reduction Development and application of big data analytics for large X-ray data sets Application of Bayesian methods to X-ray data Combinatorial analysis of various data from complementary
-
this knowledge gap and establish improved GHG models accounting for soil invertebrates. To achieve this, we create a rich AI-training dataset for multi-modal inferences, combining computer-vision, environmental
-
annotation, image recognition, data extraction); Development and maintenance of statistical software tools for causal inference and open science applications. Your qualifications profile Enrolment in a
-
Bayesian belief networks; Experience in scenario development approaches, e.g. SSPs; Experience in the application of R-based analytical tools for qualitative or semi-quantitative modelling, incl. RQDA