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Job Description Are you a skilled and field-ready researcher with a passion for marine monitoring using many different methods and techniques ranging from diver observations to integrating remote
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to prototype validation and measurement activities. Document design choices, trade-offs, and experimental results in high-quality publications. The position offers the opportunity to establish an independent
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hybrid models that integrate limnological knowledge into machine learning models following the paradigm of Knowledge-Guided Machine Learning (KGML). The position is part of an on-going project
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on understanding how different excitation methods generate polarons and correlated materials in the cuprates and other quantum materials, building on our recent results in the vanadium dioxide (see Johnson et al
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an expert in the extracellular vesicle field with skills in genetic engineering of extracellular vesicles (including transient/stable transgenesis of zebrafish), live embryo imaging, and spatial
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on understanding how different excitation methods generate polarons and correlated materials in the cuprates and other quantum materials, building on our recent results in the vanadium dioxide (see Johnson et al