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Field
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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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treatment. ENDOTRAIN will train a new generation of interdisciplinary experts who merge clinical endocrinology, AI, data science, engineering, ethics and law into an integrated field of digital endocrinology
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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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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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, high school timetabling, examination timetabling, master thesis defense assignments and scheduling and student project and master’s thesis assignments. For these problems, we wish to develop an algorithm
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correction and/or mitigation. Knowledge about networking protocols and distributed algorithms. Experience in programming, e.g., in C++, Python or Matlab. Experience with quantum simulators, such as NetSquid
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of £25,726 plus a research training support grant of £20,000 and 100% fees paid. Overview This PhD project aims to develop a computationally efficient framework for the real-time prediction of river water
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addresses two intertwined goals: Improving Human Training: Developing adaptive haptic training strategies that help operators refine their skills through real-time skill estimation, multimodal feedback, and
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
Thermography. This raw dataset is needed to be processed and annotated to train supervised and unsupervised AI models. The research will aim to develop deep learning algorithms for damage classification
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Description Challenge: Uncovering the interdependency between telecommunications networks and urban infrastructures Change: Developing data analysis and modelling methods to understand the interdependency