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, deep learning Computational genomics, network modeling, spatiotemporal/functional data analysis, time-series Strong programming in R and/or Python; best practices in reproducible research Excellent
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, 3-D dosimetry, oncologic and biological imaging, automatic treatment planning, radiomics and deep-learning, modeling of radiation damage for normal tissues and of tumor control using radiation
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with a deep interest in the fundamental mechanisms shaping plant communities and their response to climate change. Qualifications: • PhD in Ecology or a related field • Strong quantitative background
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knowledge to real-world circumstances. Candidates must have a PhD, J.D., or other terminal degree in their academic discipline to be able to teach a graduate-level course. Candidates with an MA plus 20 years
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etc; Candidates with multidisciplinary backgrounds are welcome. · Strong skills in computational and data analytical methodology development and implementation; experience in machine learning and deep
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, balancing ambition with realism. · Promote excellence across undergraduate, master’s, and PhD programs, emphasizing experiential learning, data-driven pedagogy, hands-on design, and interdisciplinarity
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, statistics/machine learning experts, clinicians/clinical researchers, and software developers to build valuable technology solutions that are scalable both within the Duke clinical enterprise as well as more
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healthcare. Qualifications Required: PhD (or equivalent) in computer science, statistics, biostatistics, electrical/biomedical engineering, or related quantitative field. Strong background in machine learning