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one from your current graduate or clinical residency training program. Graduate-level academic transcripts (unofficial is acceptable) Two writing samples, preferably a copy of a previously published
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scales. 30% -Develop research about the integration of physically-informed AI/DL models with climate and hydrologic datasets (e.g., reanalysis, satellite, and observational networks). 20% -Prepare high
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with Owen-Smith and other members of the IRIS team. Familiarity and demonstrated expertise with network and computational science methods, science of science research, creation and manipulation of large
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they are developing Required Qualifications* PhD Degree in Engineering, Computer Science, Data Science, Applied Mathematics, Statistics, or a related field Familiarity with (biomedical) signal processing Experience
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that will define the CNRE. CNRE research is both computational and experimental; we work on exciting problems in diverse areas such as bio-fluid interactions, signatures, wave energy, advanced materials
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learning, teaching, and scholarship through application of technologies and knowledge of the latest digital research methods with diverse teams. You will join a network of functional and subject experts
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one from your current graduate or clinical residency training program. Graduate-level academic transcripts (unofficial is acceptable) Two writing samples, preferably a copy of a previously published
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Qualifications* PhD Degree in Engineering, Computer Science, Data Science, Applied Mathematics, Statistics, or a related field Familiarity with (biomedical) signal processing Experience working with clinical data
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/30929265/ ). This MIP Postdoctoral Scholars program has significant resources to promote professional development, skill-based workshops, and community networking events. The program also provides
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leading multiple research initiatives that leverage imaging and computational methods to address critical challenges in urology. Ongoing efforts include the development of dynamic contrast-enhanced