19 algorithm-"DIFFER"-"NTNU---Norwegian-University-of-Science-and-Technology" PhD positions in Germany
Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Forschungszentrum Jülich
- Technical University of Munich
- DAAD
- Carl von Ossietzky Universität Oldenburg
- Catholic University Eichstaett-Ingolstadt
- Fraunhofer-Gesellschaft
- Heidelberg University
- Helmholtz Zentrum Hereon
- Helmholtz-Zentrum Geesthacht
- Helmholtz-Zentrum Hereon
- International PhD Programme (IPP) Mainz
- Nature Careers
- Saarland University •
- Universität Siegen
- 4 more »
- « less
-
Field
-
the 01.02.2026 at the following conditions (PhD position): 50% = 19,92 hours Pay grade 13 TV-L limited 30.11.2028 Your tasks: Develop AI algorithms for real-time fault detection, fault classification
-
of different faiths and beliefs. Grounded in the Christian view of human life, the KU aims to create an academic and educational culture of responsibility. The research group Reliable Machine Learning at the KU
-
sensors systems and UAVs at different scales. In particular, we will combine borehole and surface GPR as well as small-scale EMI measurements with root and shoot observations in controlled experiments
-
using electromagnetic induction (EMI), and ground penetrating radar (GPR) will be combined with soil sensors systems and UAVs at different scales. In particular, we will combine borehole and surface GPR
-
(ECLECTX team). This person occupying this position is planned to work on modeling computing elements, established and emerging, at different levels of abstraction, design and development simulation tools
-
. It is not feasible to scan the full volume of such samples at the highest desired resolution. Therefore, we require an imaging scheme that acquires relevant features at different length scales and
-
algorithms to compute similarity between interaction interfaces across millions of comparisons. This hinders identification of novel modes of protein binding, i.e. those predicted by AlphaFold, and it hinders
-
EU MSCA doctoral (PhD) position in Materials Engineering with focus on computational optimization of
quality. Secondly, different machine learning strategies based on traditional supervised learning techniques (e. g. random forest (RF), artificial neural network (ANN)) will be applied using the parameters
-
of algorithms and digital neuromorphic hardware is an additional avenue for enhancing the efficiency of the methods. In this context the research will explore digital, event-based implementations
-
. This is because experimental techniques to solve structures of protein complexes favor more stable interactions with larger interfaces and because we lack efficient algorithms to compute similarity between