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Field
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and computing, to apply. One position will focus on the scaling, calibration, operation, and tuning of spin qubit arrays using algorithmic techniques, as part of an international project, with
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position to develop and apply advanced analysis methods, including artificial intelligence and machine learning algorithms and approaches, for x-ray science and instruments. These methods will accelerate
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data, metabolomics and/or proteomics. Develops robust pipelines for data annotation, analysis, and quality control. Creates analytical algorithms and tools to address scientific questions with big data
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Software-Defined Networking (SDN) solutions to dynamically manage network congestion and improve communication efficiency. Research and develop topology-aware collective communication algorithms to optimize
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-of-the-art semantic and instance segmentation algorithms for 3D and 4D microtomography data. The project has a particular focus towards analysing fibre-based materials but will also consider other material
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research involving biological data analysis and modeling of biological systems. In particular, they will develop and apply algorithms to construct discrete dynamic models of signal transduction networks
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development as well as field data collection at multiple test sites in Ethiopia. Job assignments The successful candidate will join a large, collaborative team of researchers with expertise in electromagnetic
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investigate how machine-learning based algorithms can be used to personalize the user experience. The goal of this personalized user experience is to enable each individual user to discover their own
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neurophysiological biomarkers with long-term neural activity recording and artificial intelligence algorithms to for conditions such as pain, Parkinson’s disease, sleep disorders, Alzheimer’s disease (AD), and
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control protocols, and hybrid quantum-classical algorithms. o Modeling and benchmarking atomic qubit architectures. · Collaboration: Work closely with experimentalists to design and optimize protocols