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that come in touch with human skin can serve as vehicles for transport of diseases and their spread throughout human communities. This infection process can be mitigated by surfaces on which microbes cannot
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Posting Details Position Details Title Postdoctoral Fellow in Inner-Ear Biology Specific Title Appointment Type Postdoctoral Fellow Department IUSM - Otolaryngology-Head & Neck Surgery Campus IU
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. To set up and analyze experiments and datasets under different conditions. To propose a methodology/framework in a software prototype to be developed in the project. To report research findings in a form of
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. Desired Qualifications* Experience with fluorescence imaging, electrical stimulation, computational modeling, image processing. Modes of Work Positions that are eligible for hybrid or mobile/remote work
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a focus on synaptic plasticity, NMDA receptor signaling, 2-photon optogenetics, and advanced 2-photon imaging. We are particularly interested in candidates with strong expertise in whole-cell patch
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involving speech/audio, images, and video along with text-based applications. Job Requirements: MSc (Research Associate) or PhD (Research Fellow) in Electrical Engineering, Computer Science, Statistics
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. Set up and analyze experiments and datasets under different conditions. To propose a methodology/framework in a software prototype to be developed in the project. To report research findings in a form of
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Please apply online and attach your resume (including a list of two referees), and a separate cover letter that outlines how you meet the selection criteria below: Essential Selection Criteria: PhD in
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MACQUARIE UNIVERSITY - SYDNEY AUSTRALIA | North Ryde, New South Wales | Australia | about 1 month ago
to Apply Please apply online and attach your resume (including a list of two referees), and a separate cover letter that outlines how you meet the selection criteria below: Essential Selection Criteria: PhD
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the role Overview of the role We are seeking a highly motivated Research Fellow in Machine Learning to join the PharosAI team, focusing on developing novel machine learning methods in computer vision