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Field
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electrophysiology in ex-vivo mammalian retina. Record of publication in retinal research. Experience with fluorescence imaging, electrical stimulation, computational modeling, image processing. Michigan Medicine
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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
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scientists, from young talents to established researchers, across machine learning, statistics, logic, language technology, and ethics. You will be also part of the Digital Signal Processing and Image Analysis
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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
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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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perturbation screens with high content molecular and imaging data to understand cellular and multi cellular combinatorial programs in cells and tissues in health and disease. You will join a highly collaborative
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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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in several tropical ocean locations. A successful candidate should have: A PhD (or equivalent) in geochemistry. Experience in the operation of single and/or multi-collector plasma mass spectrometer
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developing machine learning or data science approaches for patient stratification and genetic association analyses using cardiac magnetic resonance imaging in biobank populations. Successful applicants will
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two referees), a statement of research interests and achievements. Selection Criteria: A PhD in analytical biochemistry, biosensors, nanobiotechnology or equivalent qualifications; Ability to undertake