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, enabling algorithm–circuit co-optimization across the computing pipeline with respect to key metrics such as power consumption, computational delay, and area efficiency. Beyond circuit prototyping
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of superconducting qubits to quantify performance and identify limiting physical mechanisms Perform quantum device calibrations, benchmarking, and run quantum algorithms Presenting and publishing the research
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-following inverters. Implementing and optimizing scalable algorithms for transient and stability analyses on HPC architectures (CPU, GPU, hybrid). Enhancing the numerical robustness and efficiency of existing
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or functional properties. Collaborating closely with experimental partners to integrate decision-making algorithms into real scientific workflows. Publishing results in high-impact machine learning and
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Conduct comparative benchmarking and performance analysis against state-of-the-art studies Perform numerical modeling and validation of brain-inspired and neuromorphic algorithms Design, set up, and operate
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algorithms, computational complexity theory, and information theory Relevant coursework and experience in spiking neural networks, and statistics A strong electronics background, including experience in
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(rhizotron facility) and field trials. In addition to field applications, novel inversion algorithms for ground-penetrating radar (GPR) and electromagnetic (EM) will be developed. These algorithms will enable
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science, physics, or related fields Coursework in algorithms, computational complexity theory, and information theory Relevant coursework and experience in spiking neural networks, and statistics A strong
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Perform numerical modeling and validation of brain-inspired and neuromorphic algorithms Design, set up, and operate experimental systems for circuit-level measurements and data analysis Your Profile