Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Forschungszentrum Jülich
- Technical University of Munich
- Leibniz
- Ludwig-Maximilians-Universität München •
- Technische Universität Dortmund
- Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung
- DAAD
- GFZ Helmholtz-Zentrum für Geoforschung
- Hannover Medical School •
- Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association
- Helmholtz-Zentrum Hereon
- Helmholtz-Zentrum für Infektionsforschung GmbH
- Max Planck Institute for Human Cognitive and Brain Sciences •
- Max Planck Institute for Mathematics in the Sciences
- Max Planck Institute for Meteorology •
- Max Planck Institute for Molecular Genetics •
- Max Planck Institute for Plant Breeding Research •
- Max Planck Institute of Molecular Plant Physiology •
- Nature Careers
- TU Dortmund
- Technische Universität Berlin •
- Ulm University •
- University of Bremen •
- University of Göttingen •
- University of Münster •
- 15 more »
- « less
-
Field
-
to study grid stability, fault propagation, and recovery dynamics. Analyzing control and protection strategies using high-resolution time-domain models. Developing dynamic models for grid-forming and grid
-
Your Job: Research: employ on quantum field theory in curved spacetime to model photon kinematics Output: publish in peer reviewed journals, seek patent applications when possible Dissemination
-
electrical or mechanical engineering Strong mathematical skills Experience in modelling energy systems Very good knowledge and experience in programming (e.g. Python, Matlab, C, C++) Fluent in written and
-
, medical informatics, databases, data mining, machine learning, applied mathematics, biomedical modelling and analysis of complex networks. Joint data science projects between the different partners
-
of systemic neurosciences: single cells to complex systems system analysis to mathematical modelling perception and cognition to mind and neurophilosophy biology to technical solutions Additional support is
-
strategies that use learned representations to guide data acquisition under cost and uncertainty constraints. Building surrogate models that connect imaging-derived representations with downstream physical
-
with high-dimensional, often noisy, data sets; and mathematical modelling approaches that reduce the dimensionality of parameter spaces and produce mechanistically realistic, experimentally testable
-
embedded in the Bremen Research Cluster for Dynamics in Logistics (LogDynamics) (http://www.logdynamics.de ). LogDynamics is a cooperative network of research groups from five different departments
-
the form of graphs to analyze and predict food-effector systems. Key Responsibilities Develop Probabilistic Machine Learning Models to integrate graphs and food-related omics data Multi-omics integration
-
Your Job: Maintain, and update quantitative methods for assessing economic impacts of the energy transition at the national and regional levels Develop dynamic and multisectoral economic models