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the shallow subsurface (<10 meters depth). Experience with soil moisture/salinity and sapflow sensors. Experience using neural networks and machine learning tools. Stipend $70,000.00 – $80,000.00 Yearly Point
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of at least some of the following: – Extensive independent research experience – Creativity and independence – Experience analyzing hyperspectral data and developing machine learning models - Genetic
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machine learning approaches relevant to breast cancer research and medical imaging, where appropriate collaborate with multidisciplinary teams including radiologists, radiographers, clinicians
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The DeepWave industry-funded consortium is looking for two outstanding postdoctoral researchers to undertake impactful research on the development and application of cutting-edge machine (deep
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improved process understanding. Development of open-source tools for training and optimization of machine learning surrogates. Interacting with multiple faculty members within the department, as
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the characterization, safety, biocompatibility, and performance of nanomaterials used in regulated products. Learning Objectives: You will engage in structured research training under the mentorship of FDA scientists
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Engineering, Biomedical Engineering, Medical Imaging, Signal Processing, Applied Physics, Computer Engineering, or a closely related discipline. Strong background in at least one of the following: ultrasound
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data-driven engineering methods, particularly those leveraging artificial intelligence or machine learning. Key Responsibilities & Accountabilities 1. Initiate, Execute, and Complete Advanced
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fellows are expected to submit a career development plan, specifying career goals and the competencies that the postdoctoral fellow should acquire, no later than one month after commencement of
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or photogrammetry methods, in combination with data science approaches such as machine learning and data assimilation via cryospheric models. A main focus of this work is snow and glaciers in the mountains around the