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Field
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state-of-the-art lab facilities. You will closely collaborate with other PhD students working on blue-light TFLN integrated photonics platform. The project will among others consist of the following tasks
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with colleagues responsible for downstream AI-based optimization. The ideal candidate has a strong background in computational electromagnetics and photonics, ideally with experience in topology
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close collaboration with colleagues responsible for downstream AI-based optimization. The ideal candidate has a strong background in computational electromagnetics and photonics, ideally with experience
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cavity quantum optomechanics that combines strong light-matter coupling with strong exciton-phonon interactions in a single system. The tri-partite exciton-phonon-photon interactions within a single high-Q
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use of the idea of a copper mirror in connection with dielectric layers inside a strong magnetic field that boosts the axion to photon conversion to a detectable rate in the microwave frequency regime
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Education and Experience: PhD in Physics, Optics, or Photonics Required Knowledge, Skills, and Abilities: Strong publication skills Excellent scientific writing ability and good communication skills Knowledge
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, or single-photon detectors (used for single-photon Lidar), that natively produce event-like data that is compatible with spiking networks. Similarly, detection events from RF (radar and electronic
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processing in the mammalian cochlea in vivo , and how these influence central auditory neuronal pathways. The project will primarily involve using in vivo 2-photon imaging and AAV-gene delivery applied to a
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, imaging and timing applications. In this project, we will: Develop Bayesian deep learning methods for event-based data, including single-photon detections and neuromorphic camera data. Investigate Bayesian
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for postdoctoral researchers is provided through the Office of Postdoctoral Affairs, Career Center, Teaching Center, and campus groups. Applicants should be recent PhD graduates in Neuroscience or related fields