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focused on the challenge of accelerating ternary neural networks using FPGA devices. The successful candidate will have significant experience in machine learning, FPGA design and an outstanding track
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, signal processing, wireless/optical communications, and communication system engineering Extensive experience in physical layer algorithm design and performance analysis Proven track record of publications
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ternary neural networks using FPGA devices. The successful candidate will have significant experience in machine learning, FPGA design and an outstanding track record in conducting machine learning research
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of separation technologies for energy and critical resources. Key Responsibilities: Design, execute, and analyze experiments on capacitive deionization for critical materials recovery. Design and implement
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computation. Prior experience with DNA strand design or molecular computing is desirable. You should be able to plan and execute your own research, engage in scientific discussions, and work as part of a
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hands‑on cell culture experience (≥3 years) Strong publication record commensurate with experience; excellent scientific writing and communication skills in English Solid grasp of experimental design and
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Familiarity with optimization algorithms and design of experiments methodologies Experience with high-performance computing environments Track record of publications in peer-reviewed journals Previous
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operate normally. Responsible for the establishment and improvement of equipment management system, including the use of norms, safety operating procedures. 2. Experiment Design and Execution: Design and
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on-demand control of genetically targeted neurons and astrocytes.More information about the lab can be found at: https://people.eecs.berkeley.edu/~chunlei.liu/ Key Responsibilities Design and conduct
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research student in an engineering/virtual lab. With excellent communication skills, the candidate will have expertise in the design and execution of engineering experiments but also in the design and