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emphasis on the social, economic, and policy implications of demographic shifts. The centre is internationally recognized for its expertise in analytical demography, demographic modelling, and forecasting
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often related to domesticated species and humans, but increasingly also on other organisms. Our focus areas include quantitative genetics, deep learning, machine learning, population genetics, integrative
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will lead efforts to apply state-of-the-art AI techniques (machine learning, deep learning, generative models, etc.) to the discovery and development of new materials in critical domains: water, energy
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candidates with expertise in one or more of the following specialized areas: Machine Learning / Deep Learning Uncertainty Quantification Wind Farm Flow Modelling Wind Farm Control Wind Farm Design Wind Farm
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, including artificial intelligence (AI), machine learning, internet of things (IoT), chip design, cybersecurity, human-computer interaction, social networks, fairness, and data ethics. Our research is rooted
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, artificial intelligence (AI), machine learning, and computation have emerged as powerful digital technologies for creatively generating new design ideas and rapidly advancing formgiving methods within
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. You will also work closely together with course teams to develop data generation, data analysis, modeling, simulation, and machine learning workflows as well as develop custom data science-related
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value theory, non- and semiparametric statistics, missing data problems, causal inference, graphical models, event history analysis, benchmarking, spatio-temporal modelling, machine learning, and
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background within (at least one, preferably several of) the following fields: Biomedical circuits and systems Physiological Modelling Medical sensor and instrumentation technology Health Informatics Digital
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. The candidates will be responsible for collaboratively building up the area of supply chain digitalisation with a primary focus on data governance, artificial intelligence, and applied machine learning. Successful