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Field
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experience with design and manufacturing; research experience in ergonomics; hands on experience with robotic hardware and tool usage in a field environment; proficient in design software using solidworks, 3-D
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Because of the drastically increasing demand from AI/ML applications, the computing hardware industry has gravitated towards data formats narrower than the IEEE double format that most computational
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design for different RF bands (FR3, MMW, sub-THz/THz) Analog/digital/hybrid beamforming Integrated sensing and communication Reconfigurable intelligent surfaces Hardware-constrained signal processing
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research on the design and development of next-generation wireless communication systems. Specific topics include, but are not limited to, waveform design for the THz spectrum under hardware constraints
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: Design and iterate custom-built single-molecule measurement platforms SWNT FET biosensors. Hardware Integration: Apply basic electrical engineering principles to interface biological sensors with low-noise
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, tape-out, and testing, preferably with applications to AI systems ● Design, analysis, and modeling of AI hardware such as deep neural network accelerators or neuromorphic computing. ● Emerging AI
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, tape-out, and testing, preferably with applications to AI systems ● Design, analysis, and modeling of AI hardware such as deep neural network accelerators or neuromorphic computing. ● Emerging AI
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for greenhouses and vertical farming systems. The successful candidate will focus on robot hardware development, automation system design, machine vision, and intelligent control, supported by physics-based
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involves designing, executing, and analyzing current or future quantum simulations at the intersection of subatomic physics and quantum information science. The successful candidate will also lead peer
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of experimental quantum communication hardware development, optical memory qubit characterization, and fiber-based networking demonstrations using novel memory qubits. The goal is to employ the natural telecom