Student Assistant - Machine Learning ASIC Design

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The mission of the Instrumentation Department is to develop state-of-the-art instrumentation required for experimental research programs at Brookhaven Lab and to maintain the expertise and facilities in specialized high technology areas essential for this work. Development of facilities is motivated by present Brookhaven research programs and anticipated future directions of research. Our work has a significant impact on programs throughout the world that rely on state-of-the-art radiation detectors and readout electronics.

• Conduct research on AI/ML methods for accelerating integrated circuit (IC) design.
• Participate in the deployment and testing of AI/ML-driven IC design algorithms to both open-source and industry-standard CAD tools.
• Participate in the development of AI/ML-driven IC design algorithms that are robust to circuit noise and mismatch, hardware failures, temperature changes, and other non-ideal effects.

• B.S. degree in Electrical Engineering or a closely related field of study with a focus on IC design.
• Experience deploying AI/ML models on common software tool chains.
• Basic knowledge of digital IC design flows, including digital simulation and logic synthesis.
• Knowledge of processor architectures, compilers, neural networks, and optimization.
• Excellent oral and written communication skills

• Knowledge of both the theoretical fundamentals and applications of machine learning.
• Experience working in multidisciplinary collaborations.
• Strong research experience (e.g. as evidenced by publication record).
• Excellent programming skills.
• Ability to perform experiments using low voltage (