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Field
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. Interest in clinical algorithm development and dexterity with biostatistical coding in R or Python is a plus. The primary goal of this aspect of the CH CARE Study is to combine serially obtained somatic and
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). Modelling of electrical distribution networks with VPPs and development of grid ancillary services. Implementation and proof of concept of the control algorithms in a Power HIL environment (Smart Energy
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analysis, data science, discrete and machine learning algorithms, distributed, intelligent, and interactive systems, networks, security, and software and database systems. The department has extensive
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wide range of resources and is mostly not publicly available. While sharing proprietary data to train machine learning models is not an option, training models on multiple distributed data sources
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trustworthy medical AI? Deep models already outperform humans on many benchmarks, yet in the clinic they remain black boxes: radiologists cannot see why an algorithm flags a lesion, and AI engineers cannot tell
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the adaptation and improvement of the algorithms required for the aggregation and provision of flexibility to the grid, the optimized management of an energy community, and the intelligent operation and demand
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is concerned with the mathematical problem of comparing and interpolating distributions of mass, for example probability distributions. The concept has lately gained increasing interest from
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wide range of resources and is mostly not publicly available. While sharing proprietary data to train machine learning models is not an option, training models on multiple distributed data sources
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for transmission or distribution grids, synchronous generators, large loads, transmission networks, etc. Develop simulation algorithms that enable large-scale simulations. Integrate (or co-simulate) grid component
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You will join the EPSRC-funded project “Behavioural Data-Driven Coalitional Control for Buildings”, pioneering distributed, data-driven control methods enabling groups of buildings to form