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various markers, and can be obtained under various experimental conditions, these data form a huge analytical challenge. Furthermore, individual predictions of relevant patient outcomes based
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, individual predictions of relevant patient outcomes based on such complex biological data remains difficult, especially in the context of rare diseases such as cystic fibrosis. So far, there is a lack of
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Job related to staff position within a Research Infrastructure? No Offer Description Welcome to Maastricht University! Do you want to understand and predict how people engage with digital health
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Welcome to Maastricht University! Do you want to understand and predict how people engage with digital health interventions using AI? Join us to turn real-world sensor and app data into smarter
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markets and congestion management. To address this question, you will develop state-of-the-art model predictive control tools to guide market participation decisions. Starting from existing models, you will
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on the participation in multiple consecutive short-term electricity markets and congestion management. To address this question, you will develop state-of-the-art model predictive control tools to guide market
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We are looking for a talented and enthusiastic candidate for a fully funded 4-year PhD position. The PhD candidate for this project will be working at the RNA Structural Ensemble Dynamics group led
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you eager to make AI more sustainable? As a PhD Candidate, you will develop innovative methods for predicting and reducing the energy consumption of large-scale AI systems during their design phase
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for donor kidneys. Central to this is the use of machine learning to evaluate the predictive value of biomarkers from various sources: donor-related data, perfusion fluid, and kidney biopsies. Kidney biopsies
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that can accurately predict component health and optimize repair decisions. You will develop novel data-centric approaches to Remaining Useful Life (RUL) prediction that goes beyond traditional model-focused