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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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collaboration in optimising data analysis algorithms for the raw detector data, including improving position reconstruction and pulse-shape discrimination algorithms which can be implemented on in the front-end
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information of the data to make a prediction using advanced mathematical tools. This insight opens the door for enjoying the real world. The candidate further develops efficient and robust algorithms
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develops efficient and robust algorithms for realistic settings in terms of data and computing resources and collaborates to address major challenges in important applications including marine domain and
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mathematical modelling tools. Excellent knowledge of programming languages such as R, Python, Julia, etc. Familiarity with AI algorithms and Machine Learning Fluent oral and written communication skills in
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technological progress in our increasingly digital, data-driven world. Researchers in Integreat develop theories, methods, models, and algorithms that integrate general and domain-specific knowledge with data. By
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develops efficient and robust algorithms for realistic settings in terms of data and computing resources and collaborates to address major challenges in important applications including marine domain and
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the real world. The candidate further develops efficient and robust algorithms for realistic settings in terms of data and computing resources and collaborates to address major challenges in important
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with AI algorithms and Machine Learning Fluent oral and written communication skills in English Desired qualifications: Experience with research on epidemiological modelling, with an emphasis on zoonotic
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. The NeSys laboratory has a leading role in the Data Services and Atlas Services of the EBRAINS Research Infrastructure - the European distributed research infrastructure for brain and brain-inspired research