Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Technical University of Munich
- DAAD
- Forschungszentrum Jülich
- Nature Careers
- RWTH Aachen University
- Fraunhofer-Gesellschaft
- GFZ Helmholtz Centre for Geosciences
- Leibniz
- University of Potsdam •
- Deutsches Elektronen-Synchrotron DESY •
- Forschungsinstitut für Nutztierbiologie (FBN)
- Heraeus Covantics
- Karlsruher Institut für Technologie (KIT)
- Leibniz-Institute for Plant Genetics and Crop Plant Research
- Ludwig-Maximilians-Universität München •
- Max Planck Institute for Molecular Genetics •
- Max Planck Institutes
- Ruhr-Universität Bochum •
- Saarland University •
- TU Dresden
- Technische Universitaet Darmstadt
- University of Bremen •
- Universität Düsseldorf
- 13 more »
- « less
-
Field
-
of software interfaces and data models Selection and configuration of algorithms for annotating and organizing research data and software using state-of-the-art AI technologies Ensuring the sustainability and
-
qualification (usually PhD). Tasks: The aim of the project is to design, model, fabricate and test a wireless micro-sensor which uses magnetic fields for sensing in biological soft tissues. For further
-
Infrastructure? No Offer Description Work group: PGI-15 - Neuromorphic Software Eco System Area of research: Promotion Job description: Your Job: The conventional, manual co-design of algorithms and hardware is
-
Your Job: The conventional, manual co-design of algorithms and hardware is slow and inefficient. Our group develops methods and tools to automate the co-design process. The core of this project is
-
, modelling and simulation of photonic systems, sensor systems, signal processing and device manufacturing, development of machine learning algorithms, and design of optical communication networks or power
-
Environment (VTE) for disaster response simulation, integration of Building Information Modelling (BIM) with Structural Health Monitoring (SHM) using smart sensor networks, and resilience-informed design
-
play a central role in this interdisciplinary initiative. They will: Develop and apply machine learning (ML) methods – including surrogate modeling, feature extraction, and inverse design algorithms
-
Virtual Training Environment (VTE) for disaster response simulation, integration of Building Information Modelling (BIM) with Structural Health Monitoring (SHM) using smart sensor networks, and resilience
-
for Surface Chemistry and In Situ/Operando Spectroscopy, led by Prof. Christian Hess, is a multidisciplinary research group that works on understanding the mode of operation of catalysts, gas sensors and
-
Environment (VTE) for disaster response simulation, integration of Building Information Modelling (BIM) with Structural Health Monitoring (SHM) using smart sensor networks, and resilience-informed design