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qubit-based quantum processors and connect them via a campus-scale fiber-optic network. The postdocs will design and fabricate superconducting transmon qubits and microwave-optical quantum transducers and
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automated TEM specimen preparation, including focused ion beam (FIB) methods Curate and prepare datasets for AI model training, validation, and inference Disseminate findings through high-impact publications
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computational scientists to advance a next-generation, user-friendly, agentic AI platform for automated data analysis, interpretation, and user interactions. The appointment is expected to last two years and the
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readout and controls (e.g., SQUID-based time- or microwave-multiplexed systems) with beamline data acquisition and control (EPICS/Bluesky). Develop and maintain data acquisition, calibration, and analysis
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for bioprocessing applications. The position will include designing automated experimental systems, electrode synthesis or surface modification, and integration of experimental findings with system-level analysis
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an exciting approach to agentic, fully autonomous thin film development using a combination of automated electroplating, in-operando measurements, and AI driven algorithms. He or she will work with a team of
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measurements. Postdocs have an initial term of 1 year and can be renewed in 1 year increments; up to a total of 3 years depending on funding and performance. The expected starting date is Q3/Q4 of 2025
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on developing a new hybrid light–matter platform that couples transition metal complexes with optical microcavities to achieve optical control over ultrafast spin conversion and charge transfer
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automation, high-throughput data acquisition, and real-time data processing, offering a unique opportunity to advance S/TEM capabilities, publish impactful research, and collaborate with a diverse group of
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, the development of innovative processes and technologies for recycling actinides to support sustainable fuel cycles, and the application of chemical and electrochemical principles to control and improve product