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of Aalborg University. Job Description This position is part of the cross-disciplinary DK-Future project – Probabilistic Geospatial Machine Learning for Predicting Future Danish Land Use under Compound Climate
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at Linköping University, where we laid the foundation for recent breakthroughs in protein structure prediction, which was later awarded the 2024 Nobel Prize in Chemistry. Since then, we have further developed
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recruitment process, can be found at https://accedtp.ac.uk/, in the ‘prospective applicants’ tab. Project overview Importance. Tropical forests cover ~15% of the world’s terrestrial surface. They play a crucial
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in disqualification. Applications are accepted on the University of West Florida career site: https://careers.uwf.edu . For assistance contact UWF Human Resources at 850.474.2694 or jobs@uwf.edu
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/unsupervised learning (regression, classification, clustering), ensemble methods, and deep learning architectures (CNNs, RNNs). Experience with explainable AI (e.g., SHAP, LIME) and radiomics preferred
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for clinical data Conduct statistical and machine learning analyses on large, complex healthcare datasets Clean, transform, and prepare high-quality analytic datasets for research Build and validate predictive
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personalizable computer replica of the immune system – to enable everyone and anyone to assess and optimize the health of their immune system and simulate and predict its future ability to respond to diseases. Why
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transcript and protein levels. Using machine learning, we will identify conserved expression profiles that predict lifespan outcomes. Guided by these insights, we will use state-of-the-art genome editing in