42 finite-element-analysis Postdoctoral positions at Conservatorio di Musica "Santa Cecilia" in United States
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. Electrophysiology and MRI Data Analysis of Patients with Lennox-Gastaut Syndrome About Us: Stanford Pediatric Epilepsy Research is at the forefront of research in neuroscience, focusing on understanding complex
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questions as to the short and long-term impacts on vascular disease risk. Published work from our laboratory has shown that both subcutaneous infusion of the major tobacco component, nicotine, and inhaled e
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chain network analysis and geospatial modeling. The successful candidate will have strong data science skills, including experience working with large, complex data from varied sources, and machine
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personalized learning experiences that are both effective and engaging. The first component of this work is to develop AI-augmented tools that enable elementary school-aged children to rapidly create
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& Brian Hargreaves. Partial list of applicable skills: Expertise in MRI physics Experience with raw MRI data management Experience with MRI reconstruction Clinical studies: data collection / analysis Pulse
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. Required Qualifications: A doctoral degree (PhD, MD, or equivalent) conferred by the start date. Proficiency in R/Python Experience with scRNAseq, and/or spatial proteomic/transcriptomic data analysis Growth
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learning experts will be an essential and enriching component of the position. Strong candidates will have a background in machine learning and natural language processing (NLP), with a demonstrated ability
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given to candidates studying early China using analytical methods such as zooarchaeology, paleobotany, ceramic analysis, and lithic analysis. The successful candidate will be expected to: Teach one course
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major role both in physics data analysis and in hardware/electronics work on the CMS Phase-2 muon detector upgrades. The selected candidate will likely need to travel to Geneva, Switzerland at various
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. Required Qualifications: Doctoral degree (PhD) conferred by start date Demonstrated experience with analysis of large health databases Training and experience in machine learning and deep learning methods