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and Machine Learning tools and algorithms to solve hydrology and water resources problems. Familiarity with high-performance computing (HPC), cloud platforms, or GPU clusters. Demonstrated ability
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, i.e., machine learning models explicitly constrained by physical laws (e.g., conservation of mass, momentum, or energy) or designed to integrate physics-based models and data-driven learning
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health records (EHR), waveforms from bedside monitors, radiology images and wearable sensors. This position offers a unique opportunity to work closely with clinicians on applications of machine learning
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of different intervention strategies on the genesis and severity of cytokine release syndrome and other side effects resulting from innate immune activation during CAR T-cell therapy. This will involve the use
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medical, dental and vision coverage effective on your very first day 2:1 Match on retirement savings Responsibilities* Researching and developing novel machine learning architectures for integration across
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health records (EHR), waveforms from bedside monitors, radiology images and wearable sensors. This position offers a unique opportunity to work closely with clinicians on applications of machine learning
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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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experiments to validate findings from the omic studies. The desired skill set is split between dry lab (bioinformatics) and wet lab (basic science/animal models). Additionally, the individual will be required
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, such as Seurat and Scanpy. Experience with machine learning models, such as transformer and diffusion models. Strong written and oral communication skills. Modes of Work Positions that are eligible