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, the position may include development of various other device architectures for nanoscale energy harvesting applications. The PhD student is expected to work independently as well as in close collaboration with
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Networks on GPUs. By optimizing code generation using GPU architecture, we will create more efficient ANNs on GPUs achieving higher inference and training performance. These faster networks will be use in
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of the flow properties of compressible colloids, microgels, combining scattering techniques with rheology. Work duties During the 4 years of this project, the PhD student will use pNIPAM-based
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