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experience in at least three of the following: developing watershed model input datasets, geospatial analysis, applying large-scale hydrologic models, artificial intelligence and machine learning, computer
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. Any appointment is conditional upon submission of documentation confirming completion of the PhD degree. solid programming skills applied to machine learning algorithms, interactive systems, audio and
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. This project involves the development and application of interpretable machine learning methods to uncover allosteric regulation of disordered regions in the dynamics of G-protein coupled receptors to enable
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machine learning, spatial audio and audio-visual AI into groundbreaking creative technology. About you We seek a talented Research Fellow to investigate generative audio AI technology for production
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What You’ll Need: PhD in computer science, artificial intelligence, machine learning, computational biology, biomedical engineering, or a closely related quantitative field. Strong foundation in modern
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and energy materials. Preference will be given to those with knowledge of computer programming, AI and/or machining learning. Applicants are invited to contact Prof. Jianguo Lin at telephone number 2766
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As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the opportunity to be equipped with applied research skill sets
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behaving mice, and advanced modeling + machine learning analyses. Please read more about our research at www.apostolideslab.org . Key questions we want to answer are: How do neural circuits extract
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of lab-scale and pilot-scale experiments/operations with element of machine learning, sample characterizations, data analysis, and so on. Job Requirements: PhD degree in Materials Science, Polymer Science
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basic experience in machine learning or computer vision libraries; familiarity with Vision-Language Models (e.g., CLIP, BLIP) or scene-graph inference is a plus. Key Competencies Strong software