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biogeography. A key focus lies in comparing past and present natural processes for predicting environmental changes. Start of studies in the winter semester (October) Opening of applications and publication
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linear models Knowledge and implementation of machine/statistical learning methodology (predictive modeling workflow) R package development experience Demonstrated experience with Tableau (or Power BI
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(2024) https://www.nature.com/articles/s41591-023-02702-z Prediction models for diagnosis and prognosis of covid-19: systematic review and critical appraisal. https://pmc.ncbi.nlm.nih.gov/articles
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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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trends and analyze internally and externally produced data. Build and present sophisticated models to predict and assess the likelihood of various outcomes. Strategic Initiatives (25%) Advance new programs
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candidate will be expected to teach interdisciplinary courses in our Computation & Design major, including Computational Social Science, Machine Learning for Social Science, Modeling and Predicting, and
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Researcher for the Mechanical Systems Modeling (MSM) Group. The Electric Motor Researcher will conduct detailed analysis of electric motors and motor drive systems used in gas centrifuge applications
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of complex epidemiological and genetic data, in computational and population health sciences and in disease risk-modelling and risk-prediction. Eligibility criteria The project will suit students with strong
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models ignore this exposome. In BEE, we will build explainable, physics-guided, GeoAI-driven models that: Predict acute and chronic NCD risks at the population scale Identify vulnerable neighbourhoods and
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: 3D model learning, prediction models from imaging and molecular data, model-based simulation coupling, and uncertainty-aware outputs for lab/clinical validation. Work with 3D datasets, time-series