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a role model and fostering an inclusive working culture. Person Specification PhD, or close to completion, in a relevant, quantitative field, e.g. meteorology, machine learning, climate science
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of artificial intelligence and behavioral neuroscience. This individual will join our interdisciplinary team of computer scientists and behavioral neuroscientists seeking to identify the mechanistic and
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network engineering and angiogenesis 3). Applications of machine learning in cell and tissue engineering Candidates should have demonstrated publication records in cardiac and vascular engineering or
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++, or Go, and frameworks like PyTorch or TensorFlow, is highly advantageous. Experience in developing and deploying machine learning models, particularly in natural language processing (NLP) and large
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and Machine Learning, with a focus on studying geometric structures in data and models and how to leverage such structure for the design of efficient machine learning algorithms with provable guarantees
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projects on metabolic diseases * Develop and apply machine learning models for biomarker discovery, patient stratification, and prediction of disease trajectories * Collaborate with clinicians
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integration Key areas: § Metagenomic and 16S rRNA sequencing analysis § Single-cell RNA-seq and proteomic/metabolomic data integration § Machine learning and AI applications in microbiome data
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machine learning models with respect to accuracy and uncertainty quantification. - Developing software to implement the goals stated above (most likely in Python). - Disseminating results
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Bioinformatics, as well as the Departments of Biostatistics & Biomedical Engineering, University of Michigan is seeking a postdoctoral fellow for bioinformatics problems involving quantum machine learning and
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machine learning/AI or cybersecurity, or both, as evidenced by a strong track record of publications in leading journals and conferences in relevant areas. Software programming skills. To be successful