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. The successful candidate should apply state-of-the-art methods in either aquatic ecology and biodiversity research (e.g., environmental omics, eDNA, etc.) or hydrology (e.g. integrated modeling and/or AI-based
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-scale genomic and phenotypic datasets (e.g., PheWAS, statistical genetics, prediction models) Analyze high-dimensional data from biobanks and clinical information systems Contribute to teaching activities
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simulations of compact binaries (including, for example, binary black holes, binary neutron stars, and black hole–neutron star binaries). The broader goals are to generate accurate predictions for gravitational
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will develop and evaluate new approaches to predicting current and future population exposure to such hazards by combining numerical modelling and remote sensing of river migration, with machine learning
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, or predictive modelling. • Experience working with secure research environments (e.g., TREs, data enclaves). Applicants should send the following documents during the application: a. Cover letter highlighting
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materials to enhance the cell robustness. Work plan The work plan for the PhD thesis will be divided in three main steps: 1) A chemo-mechanical model will be built to predict the crack initiation and
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anticipating crises. Current landslide prediction models, based mainly on rainfall thresholds, become ineffective in the presence of snow cover. Snow acts as a temporary reservoir, storing precipitation before
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including forecasting models to predict the expected distribution of pests on the field to landscape scale. The research is expected to make pest forecasts and link them to the existing expertise in crop
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modelling photonic devices and physical reservoir computing systems. The activities within the project will benefit from synergies with other projects in the group as well as with other activities
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health. Please see our website for more information: gvnlab.bme.columbia.edu We expect the Staff Associate III to lead the development and application of advanced computational models to simulate, predict