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hardware. As part of our team, you will perform research to develop new scalable quantum simulation algorithms, based on multi-linear representation theory, and apply them to real world applications spanning
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hardware architects to establish how agentic AI and these languages co‑design with heterogeneous HPC systems (CPUs, GPUs, PIM, AI accelerators). Study performance and portability tradeoffs, leveraging
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research spanning detector simulation, Spiking Neural Network (SNN) design, neuromorphic hardware, and data-rich experimental systems such as CMS pixel detectors, Timepix4, and novel photodetector
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characterize radiated emissions from transmitters of interest Provide feedback on signal quality/attributes of collected data to support hardware development efforts Support planning of experimental campaigns
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electronics. Experience in C/C++, Matlab, and Python programming. Experience in power systems software like PSCAD, PSS/e. Preferred Qualifications: Experience in real-time simulation hardware like Opal-RT and
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implementation on hybrid quantum-classical hardware, and collaboration with a multidisciplinary team of researchers in quantum computing and computational condensed matter physics. The ideal candidate will have a
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research within past five years. Preferred Qualifications: Ability to work independently to design and deploy methods at scale. Familiarity with hardware-software co-design, memory hierarchies (DDR, HBM
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the last five years. Preferred Qualifications: Background in in-situ process monitoring for metal AM, particularly DED. Hands-on experience with sensor hardware and data acquisition systems. Experience with