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is using state of the art machine learning tools to extract interpretable latent dynamics. We seek a highly motivated PhD student to develop a predictive computational model using recurrent neural
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applications. To achieve this, you will employ computational fluid dynamics (CFD) and machine learning (ML) to investigate degradation mechanisms under various operating conditions and develop strategies
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Brandenburg University of Technology Cottbus-Senftenberg • | Cottbus, Brandenburg | Germany | about 22 hours ago
Degree Doctor of Philosophy (PhD) in Heritage Studies Course location Cottbus Teaching language English Languages All courses are taught in English. The dissertation is written in English, and the
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, and apply modern machine learning approaches yielding hybrid and reduced order models to enable real-time applications. In collaborating with industrial partners you will integrate real-world data and
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architecture exploration, hardware/software co-design and operating/runtime systems. Typical application domains are e.g. signal-/image processing, artificial intelligence and machine learning. Tasks: research
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approaches and will integrate novel hardware (including electrode arrays, microdevices, analytical systems) into automated robotic pipelines You will also apply machine learning-based analyses to imaging and
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Dresden, Sachsen | Germany | about 2 months ago
PhD in the field of Medical Physics or comparable applied/natural science # Profound knowledge in machine-learning and strong affinity to apply this in the field of radiotherapy # Expertise in
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The Hamburg Centre for Ultrafast Imaging (CUI), Cluster of Excellence | Hamburg, Hamburg | Germany | about 2 months ago
in a relevant field. You are experienced in the theory of light-matter interactions. In addition, you have expertise in machine learning, or in electronic-structure theory, or in molecular-dynamics
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PhD Student (gn*) Job Id: 11029 Limited to 3 years | Part-Time with 65% | Salary according to TV-L E13 | Institute of Molecular Tumor Biology We are UKM. We have a clear social mission and, with
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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Bremerhaven, Bremen | Germany | 2 months ago
this PhD, we propose to apply statistical computing combined with machine learning (ML) to the spectrophotometric data to derive high-resolution information on CDOM absorption and its origin. This will be