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point-based PhorEau projections using a machine-learning model predicting tree species richness as a function of spatially explicit abiotic and biotic covariates, including satellite-derived data
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to generate baseline datasets for calibrating and validating predictive models of biodiversity-rich forests. Using machine learning (ML) algorithms, the Research Assistant will help predict the occurrence
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, informative monitoring and diagnosis of model drift, and cross-platform efficiency. Implement and maintain best-in-class data solutions, managing machine learning models from deployment to retirement, ensuring
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, proteomics, metabolomics), Capacity to develop and/or apply : Statistical or mathematical models Machine learning / AI methods Systems biology modeling approaches Research position The fellow will conduct
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, informative monitoring and diagnosis of model drift, and cross-platform efficiency. Implement and maintain best-in-class data solutions, managing machine learning models from deployment to retirement, ensuring
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Your Job: We are looking for a PhD student to contribute to the development of fast, accurate, and physics-informed machine learning models for predicting blood flow in patient-specific vascular
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Intelligence & Machine Learning Engineer/Scientist I works within the Artificial Intelligence Operations and Data Science Services group (AIOS) in the Informatics & Analytics department of Dana-Farber Cancer
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complementary data from other Mars missions to strengthen current models and provide comparative insights that enhance research conclusions from Hope observations. Develop Machine Learning methods and run
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, development, and training of machine learning and deep learning algorithms. Creation of accurate, robust, and energy-efficient models. Development of systems capable of predicting and making decisions in real
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clinical approaches, including: Histopathology and digital pathology (whole-slide imaging, WSI) Quantitative analysis of the tumour immune microenvironment AI-based image analysis, machine learning and deep