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Field
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intermittent. The PhD will work will be twofold. The first part will be to improve and develop datasets and estimation algorithms for renewable energy that will enhance the simulation capabilities of the open
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applying interpretable AI / machine learning / deep learning / information-theoretic methods and algorithms in the context of multiscale biological networks, ranging from molecules (protein chemistry) to
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research on designing mobile energy hubs, energy systems integration, resilience analysis, and developing digital twin models and AI-enabled algorithms. You will conduct lab and field tests, analyse data
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, and an optical multi-pass cell (around the PA cavity) to increase signal levels. The PARS sensor will be developed and tested for real-world outdoor usage with an eye to developing a commercial product
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and Machine Learning, with a focus on studying geometric structures in data and models and how to leverage such structure for the design of efficient machine learning algorithms with provable guarantees
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an L-band sensor, with scientific missions to monitor the Arctic and cryosphere. With a changing Arctic the melt season is prolonged, and with these changes to the snow-covered sea ice. Within
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, prediction, and decision support and automation. Additional duties include but are not limited to: Developing and refining algorithms and workflows for crop monitoring, modeling, prediction, and decision
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preferred, and this can take various forms: working with large model simulations or large data, compiled programming languages, algorithms, etc. The position is an especially good match for candidates
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. Combining operators You can combine the operators above to fine-tune your results: +"artificial intelligence" algorithm +robot -machine → Shows results only if they include artificial intelligence (as an
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or Mathematics or Statistics with a strong background in one or more of the following: AI, machine learning, Bayesian statistics, programming languages, logic and algorithms, formal methods, probability and