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) formed to train a new generation of 13 Doctoral Candidates (DCs) as PhD graduates in the disciplines of law, ethics or computer science with the common goal of researching methods and tools to make
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, combining experimental approaches (single molecule fluorescence and biochemistry) with computational methods. The candidate will obtain single-molecule multiplexing data and validate machine learning
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project will be to develop novel image acquisition schemes and image reconstruction algorithms for using a combination of tomographic imaging and machine-learning based techniques. You will work with real
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. Lorenzo Grassi in order to conduct research and publish the results at top-ranked international academic conferences and journals. You will be expected to collaborate with fellow PhD candidates and
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optimizations and approaches inspired by machine learning within the framework of cognitive radar; and C) verify the developed approaches with suitable simulations and experimental demonstrations. Specifically
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options, within the supervising and organisation teams, but also within the extensive project partnership, able to perform within project timescales. Competences in data analytics, machine learning / AI
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of extreme weather events and land use change on vegetation seasonality and efficiency. For this, you will develop and apply geo-artificial intelligence methods, including spatiotemporal machine learning