Overview
Define and lead the end-to-end signal integrity simulation strategy for next-generation systems, spanning room-temperature electronics, cryogenic infrastructure, Cryo-CMOS subsystems, packaging, and quantum hardware. Develop and maintain system-level models that predict signal fidelity, crosstalk, timing, noise, attenuation, and bandwidth limitations across the quantum control and readout stack. Drive architecture trade studies and design decisions through simulation-based analysis, helping teams identify risks and optimize performance before hardware implementation. Establish simulation methodologies, modeling standards, and validation practices using electromagnetic, circuit, behavioral, and system-level simulation tools. Partner closely with Cryo-CMOS, packaging, readout, and qubit design teams to define interfaces and performance requirements for future quantum platforms. Document de
Full job description
Full Job Description
Define and lead the end-to-end signal integrity simulation strategy for next-generation systems, spanning room-temperature electronics, cryogenic infrastructure, Cryo-CMOS subsystems, packaging, and quantum hardware. Develop and maintain system-level models that predict signal fidelity, crosstalk, timing, noise, attenuation, and bandwidth limitations across the quantum control and readout stack. Drive architecture trade studies and design decisions through simulation-based analysis, helping teams identify risks and optimize performance before hardware implementation. Establish simulation methodologies, modeling standards, and validation practices using electromagnetic, circuit, behavioral, and system-level simulation tools. Partner closely with Cryo-CMOS, packaging, readout, and qubit design teams to define interfaces and performance requirements for future quantum platforms. Document designs, results, and methodologies to enable reproducibility, knowledge sharing, and downstream integration Embody our Culture and Values Doctorate in Electrical Engineering, Physics, or related field AND 3+ years technical engineering experience. OR Master's Degree in Electrical Engineering, Physics, or related field AND 6+ years technical engineering experience OR Bachelor's Degree in Electrical Engineering, Physics, or related field AND 8+ years technical engineering experience Doctorate in Physics, Engineering, or related field AND 5+ years experience in industry or in a research and development environment OR Master's Degree in Physics, Engineering, or related field AND 8+ years experience in industry or in a research and development environment OR Bachelor's Degree in Physics, Engineering, or related field AND 12+ years experience in industry or in a research and development environment OR equivalent experience. Extensive experience in signal integrity, RF engineering, electromagnetic simulation, or system-level modeling. Experience developing simulations using industry-standard tools such as Cadence, Ansys HFSS, Keysight ADS, AWR, COMSOL, SPICE-based tools, or equivalent. Experience with transmission line theory, impedance matching, S-parameters, crosstalk analysis, and high-speed interconnect design. Experience developing and validating simulation models through correlation with experimental measurements. Demonstrated ability to lead technically complex cross-disciplinary projects. Experience with cryogenic electronics, Cryo-CMOS systems, superconducting systems, or quantum computing hardware. Experience modeling large multi-domain systems spanning electrical, RF, thermal, and physical interfaces. Experience with signal integrity challenges in mixed-signal, RF, or high-speed digital systems. Experience with Python-based simulation, automation, and data analysis workflows. Experience defining engineering requirements, validation plans, and system-level performance metrics. Familiarity with control and readout architectures for advanced computing systems. Experience mentoring engineers and driving technical direction across multiple teams. Ability to leverage artificial intelligence (AI) tools to drive innovation and efficiency (e.g., measurement, performance modeling and analysis, research gathering, day-to-day task automation). Ability to work in an “AI-first” environment using modern AI tools to accelerate discovery through hardware development. Ability to leverage AI tools to accelerate modeling, simulation, and engineering decision-making. Industry knowledge of advanced packaging technologies and design
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