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world and a suite of associated machine learning tools. The incumbent will be advised by Dr. Laurel Symes (CAPS, [email protected]). Depending on the research direction, collaboration and additional
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avenues of research rather than a required work plan. They may be pursued individually or in combination, and we welcome other creative and strategic approaches. Statistical or machine-learning approaches
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in our collections or on view in our galleries. We seek an individual with a passion for teaching and interdisciplinary thinking; a deep commitment to object-based learning and inquiry; and a
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studies. Strong background in AI/ML fundamentals and extensive experience with deep learning (DL) methods. Demonstrated proficiency in Python and machine learning frameworks (e.g., PyTorch, Jax, scikit
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: machine learning or deep learning, structural modeling and analysis, and genome or transcriptome analysis; have a strong record of peer-reviewed publications or equivalent scholarly output; collaborate
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experience with deep learning (DL) methods. Demonstrated proficiency in Python and machine learning frameworks (e.g., PyTorch, Jax, scikit-learn) applied to genomic/related datasets. Experience with sequence