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of high-throughput systems is maximized using design of experiment (DoE) approaches in order to efficiently explore the high-dimensional parameter space of the electrolysis processes. DoE is required
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data to design robust, efficient deep learning algorithms that maximize the information extracted from images and delivered to the robot. To be successful in this role, we are looking for candidates
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researchers to support complex behavioral experiments. Qualifications: Experience in designing and building custom optical systems. Familiarity with Zemax and CAD software. Strong programming skills in C
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The School of Engineering and Applied Sciences at Princeton University seeks applications for a postdoctoral position at the Keller Center for Innovation in Engineering Education. The position is in
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layer algorithm design and performance analysis In addition to the above qualifications, it is highly desirable that the candidate has prior research experience in one or more of the following research
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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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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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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