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the internal application process. Welcome to The Ohio State University's career site. We invite you to apply to positions of interest. In order to ensure your application is complete, you must complete
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administrative activities. This involves small scale project management, to co-ordinate multiple aspects of work to meet deadlines. Application Process Applications for this vacancy are to be made online via
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conducting clinical or preclinical proof-of-concept studies Preferred: Experience in physiological signal processing and the application of machine learning to biomedical data Background in computational
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vision research. The department fosters interdisciplinary collaboration, addressing real-world challenges through innovative machine learning, data science, and intelligent systems research. About the role
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Electrical Engineering, Computer Science, or a related field Strong background in speech processing, signal processing or machine learning Proficiency in Python and deep learning frameworks Experience with far
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related field. The ideal candidates will have experience in one or more of the following topics: deep learning for image and point cloud data processing, deep learning for time series data prediction
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desirable that the candidates have strong knowledge in at least one of the following research directions: 1) array signal processing 2) Radio channel sounding, estimation, and modelling 3) Integration design
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are seeking to appoint a Postdoctoral Research Associate with experience of structural biology techniques to join Dr Paul Elliott’s Lab to investigate the mechanisms of ubiquitin signalling within inflammation
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APPLICATION INSTRUCTIONS: CURRENT PENN STATE EMPLOYEE (faculty, staff, technical service, or student), please login to Workday to complete the internal application process . Please do not apply
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Electrical Engineering, Computer Science, or a related field Strong background in speech processing, signal processing or machine learning Proficiency in Python and deep learning frameworks Experience with far