Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- Leibniz
- Technical University of Munich
- Fraunhofer-Gesellschaft
- Georg August University of Göttingen
- Ludwig-Maximilians-Universität München •
- Helmholtz
- Deutsches Zentrum für Neurodegenerative Erkrankungen e. V. (DZNE)
- Forschungszentrum Jülich
- German Center for Neurodegenerative Diseases (DZNE)
- Hannover Medical School •
- Heidelberg University
- Helmholtz-Zentrum Potsdam - Deutsches GeoForschungsZentrum GFZ
- Nature Careers
- Academic Europe
- Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung
- BIPS
- BMW Group
- Brandenburg University of Technology Cottbus-Senftenberg
- Carl von Ossietzky University Oldenburg
- Constructor University Bremen gGmbH
- FAU Erlangen-Nürnberg •
- FBN Dummerstorf
- FIZ Karlsruhe – Leibniz-Institut für Informationsinfrastruktur
- GESIS - Leibniz Institut für Sozialwissenschaften
- Helmholtz Centre for Environmental Research - UFZ •
- Helmholtz-Centre for Environmental Research, UFZ, Multiple Stressor Ecology group of the Department of Ecotoxicology
- Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association
- Helmholtz-Zentrum Hereon
- Humboldt-Universität zu Berlin •
- International Max Planck Research School (IMPRS) for Quantum Dynamics and Control (QDC)
- Leipzig University •
- Max Planck Institute for Chemical Ecology •
- Max Planck Institute for Demographic Research (MPIDR)
- Max Planck Institute for Demographic Research, University of Manchester
- Max Planck Institute for Dynamics and Self-Organization, Göttingen
- Max Planck Institute for the Science of Light, Erlangen
- Max Planck Institute for the Study of Crime, Security and Law, Freiburg
- Max Planck Institutes
- Otto-von-Guericke-Universität Magdeburg
- University of Bonn •
- University of Cologne •
- University of Göttingen •
- University of Konstanz •
- University of Tübingen •
- Universitätsklinikum Schleswig-Holstein (UKSH)
- 35 more »
- « less
-
Field
-
Experience in plant stress ecology Experience with statistics, R Interest in team work Willingness to work in Kiel during joint experiments Desirable: Knowledge in aquatic ecology, microbiology, molecular
-
computer science, business informatics, media informatics, mathematics, applied mathematics, statistics, or a related field. Also, students from other fields with a sufficient skillset in computational
-
foundation model, Run case studies and statistical evaluations of hydrological downscaling and improve the downscaling model based on these results, Perform general research into the application of advanced
-
Engineering, Mathematics, Statistics, or related fields. • Strong programming skills in Python, Java, C++, etc. • A solid foundation in generative AI, machine learning, and related areas. • An Interest in eye
-
is expected An excellent mathematical background and experience in software development is required Experience in developing and applying statistical and/or machine learning-based computational methods
-
departments and research partners (for example, OLED technology and manufacturing) Development and implementation of Device and Test Specifications Technical and statistical evaluation of measurement results
-
departments and research partners (for example, OLED technology and manufacturing) Development and implementation of Device and Test Specifications Technical and statistical evaluation of measurement results
-
the field of computational statistics and data science Enhancing the existing R package "MicSim" for modelling intergenerational dynamics Creation of a simulation model at the person level with a focus on
-
Theory for Manifold Data and Bayesian Smeariness of Location Statistics”. The project will explore the effects of non-Euclidean geometry on Bayesian inference from a frequentist Bayesian perspective
-
Helmholtz-Zentrum Potsdam - Deutsches GeoForschungsZentrum GFZ | Potsdam, Brandenburg | Germany | about 2 months ago
to improve the current monitor capabilities of the global ocean circulation. The candidate will help to overcome fundamental problems of Earth observation inversion by using statistical and numerical modelling