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the device and for algorithm efficiency as compared to qubits. We will explore the use of tightly focused laser beams and their interaction with crystals of trapped ions to realize new ways to prepare and
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of TUD applies), preferably via the TUD SecureMail Portal https://securemail.tu-dresden.de by sending it as a single pdf file tokerstin.achtruth@tu-dresden.de orto: TU Dresden, Chair of Algorithmic and
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developing technologies for 6G? To meet the requirements of future mobile networks, network architectures need to become more agile and will include terrestrial and airborne network components linked by radio
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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
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of the following objectives: Design and development of long dwell-time, distributed signal processing algorithms for improved target detection Design and development of signal processing techniques for enhanced
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simulations and thermal comfort analyses by developing fast parametric algorithms and data-driven surrogate modelling approaches capable of predicting dynamic outdoor thermal comfort with high accuracy
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UNIVERSIDAD CATÓLICA DE MURCIA - FUNDACIÓN UNIVERSITARIA SAN ANTONIO DE MURCIA | Spain | 22 days ago
, development, and training of machine learning and deep learning algorithms. Creation of accurate, robust, and energy-efficient models. Development of systems capable of predicting and making decisions in real