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of the developed algorithms) Empirical investigation of use cases Scientific exchange and publication of results This position offers the possibility to acquire a PhD degree, which is encouraged. This research
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oriented, regionally anchored top university as it focuses on the grand challenges of the 21st century. It develops innovative solutions for the world's most pressing issues. In research and academic
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optimizing reaction conditions compared to human decision making and design of experiments techniques. We will develop a Bayesian optimization algorithm for the optimization of reaction yields
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Planning of and participation in (RMT) field experiments in Germany, Europe and worldwide Further development of the processing algorithm for RMT data and integration into the analysis software available
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numerical modeling and validation of brain-inspired algorithms Develop circuit-plausible training and inference algorithms, and analyze their behavior in LTspice and Cadence Spectre Perform algorithm–circuit
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-funded AI research group “Fusing Deep Learning and Statistics towards Understanding Structured Biomedical Data (DeSBi)” development of deep neural networks and machine learning algorithms for the analysis
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neurons. Responsibilities and tasks This PhD project aims to develop, verify, and benchmark learning rules in networks of complex spiking neuron models in the application field of geolocalization: Building
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, and training methods - across multiple technological platforms - photonics, electronics, biological neurons. Responsibilities and tasks This PhD project aims to develop, verify, and benchmark learning
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acceleration of large-scale machine learning workloads Perform characterization and modeling of electronic and optical devices Develop hardware-aware machine learning models incorporating electronic and optical
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devices Develop hardware-aware machine learning models incorporating electronic and optical device constraints Design and implement hardware-efficient training methodologies for machine learning systems