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. Demonstrated expertise in interdisciplinary research with technical and clinical teams and patients desired. Experience leveraging machine learning for human musculoskeletal biomechanics applications desired
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machine learning—for chemical and biological applications. You will design and implement models ranging from molecular to process scales, develop model-predictive control and optimization strategies, run
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data Experience with GIS/RS and database environments (e.g., ArcGIS and Quantum GIS) Experience with machine learning and statistical learning Experience working with large, diverse datasets Familiarity
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Materials Science Engineering, Electrical and Computer Engineering or Physics Required Experience: Growth and characterization of thin films; Micro- and nano-fabrication; Magneto-transport Desired Experience
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machine learning—for chemical and biological applications. You will design and implement models ranging from molecular to process scales, develop model-predictive control and optimization strategies, run
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: PhD in Engineering Desired Education: PhD in Materials Science Engineering, Electrical and Computer Engineering or Physics Required Experience: Growth and characterization of thin films; Micro- and
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-November. Required Qualifications: Candidates must hold a doctoral degree in economics, public policy and management, sociology, finance, public health, or computer/library/information sciences by the start
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the implementation of machine learning/AI methods for studying complex human diseases, such as glaucoma and retinal diseases. The candidate will have the opportunity to lead research projects, write
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engineering or related fields. Candidates should have a strong research record in LLM-based agents, reinforcement learning, or large language models, preferably in areas closely aligned with the topics outlined
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the implementation of machine learning/AI methods for studying complex human diseases, such as glaucoma and retinal diseases. The candidate will have the opportunity to lead research projects, write