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Field
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porous materials Develop novel machine learning model for predicting gas adsorption behavior Investigate molecular transport and separation mechanisms for membrane process Publish journal articles and
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are considered the largest source of uncertainty in climate predictions because it is complicated to accurately model the small-scale process (microphysics) inside clouds occurring in a range from meters to
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at unprecedented resolution. The core innovation of your work will be integrating this data to train deep learning models that predict chromatin accessibility and gene expression patterns. These models will
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attention to scientific rigor and interpretability Experience with XAI tools (SHAP, LIME, Integrated Gradients) to identify which features of the model are driving the predictions Clear written and verbal
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data to identify proteomic signatures and develop novel predictive models for Alzheimer’s, Parkinson, and Dystonia as well as to identify novel proteins and pathways implicated on disease pathogenesis
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require additional information? Please contact: Efstratios Gavves, Associate Professor, e.gavves@uva.n Where to apply Website https://www.academictransfer.com/en/jobs/359154/postdoc-on-robot-world-models-u
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Researcher to join an interdisciplinary project focused on improving early diagnosis and risk prediction in adolescents with early-onset psychosis, with particular emphasis on schizophrenia and bipolar
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the following responsibilities: ● Leading the development of predictive bioeconomic models to estimate economic outcomes, including fisheries spillover effects and biodiversity benefits, across global
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using Matlab code to estimate the appropriate channel parameters in various wave bands for the design of radio systems. Collect the data and analyse it and relate it to weather data for prediction models
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perturb sequencing to establish foundational models to predict the effects of potential drug candidates on cardiovascular diseases. By combining genome engineering, functional genomics, and tissue models