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Field
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full-stack approach to suppressing errors in quantum hardware. This research focuses on achieving practical quantum computation by integrating techniques ranging from hardware-level noise suppression
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setting up the PI’s new research lab, including hardware/software integration, experimental platforms, and safety protocols. Support preparation and submission of competitive grant proposals to federal
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FieldPhysicsYears of Research ExperienceNone Additional Information Eligibility criteria - Experience with detector hardware and knowledge in silicon-based detectors - Expertise in C++ and python programming - Strong
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of responsibility are: 1. Barrel Hadron Calorimeter Group : This includes work on the UNH test stand and commissioning of the detector, encompassing both simulation and hardware development. 2. Polarized Deuteron
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develop the first fault-tolerant quantum computers that can handle applications at realistic scales. To date, several architectures for quantum hardware have been developed that all have their strengths and
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deposition, and microfabrication methods Strong background in experimental hardware and programming skills Willingness to take responsibility for a thin-film deposition cluster, consisting of two thermal
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for real-time battery health monitoring and fault detection. Collaborate with embedded systems and hardware engineering teams to integrate AI models into the BMS. Optimize AI/ML pipelines for resource
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well as optical measurements on the platform's other instruments (infrared photoluminescence, Raman). *Development for operando and in-situ measurements, both hardware and software. *Perform data analysis
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pipelines, Mixed Reality Toolkit customization, and performance tuning under hardware constraints; collaborating on robot motion planning, path optimization, and sensor data processing algorithms
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challenge, making energy-efficient computing a critical research priority. This project addresses this challenge through a novel co-design approach that simultaneously optimizes both hardware and software