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Field
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Physics, Computer Science or closely related fields like mathematics. Excellent communication skills (including proficiency in English) as well as enthusiasm for interdisciplinary work are essential for all
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, partly due to a lack of reliable predictors of transplantation outcomes. The ADORABLE consortium aims to develop an advanced, data-driven assessment system for donor kidneys. Central to this is the use
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for graphs; 4. Practical experience in the analysis of scientific data; 5. Proficiency in programming with Python; 6. Familiarity with the drug discovery process; 7. Ability to work on interdisciplinary
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, or erroneous data, Data cleaning and generation, Development of enhanced loss functions and information-theoretic methods for optimized data analysis, Machine learning-based image segmentation of tomographic
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-equilibrium conditions. The project is a UKRI/NSF collaboration with Virginia Tech, and the use of direct numerical simulation, modelling and analysis will be complemented with experimental data from
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reasoning domains. This work will blend cutting-edge experimentation - spanning RL, few-shot learning, meta-learning, etc. - with formal analysis to push the boundaries of what modern AI systems can reliably
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. In this PhD-project, you will propose and evaluate new AI methodology to ensure that organoid data can be used to optimally predict relevant patient outcomes. You will use a real-world case study on
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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Bremerhaven, Bremen | Germany | 19 days ago
complemented by Monte Carlo simulations, triple collocation analysis and data assimilation to develop a frame work for the operational processing and data fusion to finally derive 3- dimensional (dim), and where
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Carl von Ossietzky Universität Oldenburg | Oldenburg Oldenburg, Niedersachsen | Germany | 12 days ago
team spirit Good communication skills Experience programming in python Experience in computational modeling of neural circuits and in the mathematical analysis of neural computations Research experience
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to three years or a SU PhD scholarship (4+4) for a period of up to four years in AI-based Analysis of Scandinavinist Propaganda and Public Perceptions during the Crimean War (1853-1856) provided