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have a PhD in Civil Engineering, Engineering Mechanics, or Mechanical Engineering. Applicants are expected to demonstrate research experience in the fields of structural modeling and machine-learning
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healthcare applications. We use large real-world complex datasets, including data extracted from electronic health records and medical images, for applications pertaining to patient diagnostics and prognostics
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conjugation, neuroscience, and preclinical model experiments. The candidate will work in a dynamic, multidisciplinary environment alongside PhD-level engineers and scientists, graduate students, and full-time
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models for signal transmission and reception, derivation of fundamental performance limits, algorithmic-level system design, and performance evaluation through computer simulations and/or experimental
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of performance limits, algorithmic-level system design and performance evaluation via computer simulations and/or experimental means. The PDA is expected to actively disseminate results through publications in
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expertise in these areas is highly encouraged. The selected candidate will work on cutting edge technologies in an excellent research environment, with a potential to work with a Quantum Computer through our
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machine learning. The successful applicant will participate in research involving human computation, knowledge discovery, machine learning, and data science. The position will provide the opportunity
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environment consisting of PhD scientists, graduate students, and undergraduate students. Applicants must have a PhD in chemistry or materials science. Excellent experimental and synthetic skills relevant
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aims to identify biomarkers in the eye and brain that explain vision loss, building on our previously-developed method linking clinical, neural and behavioral data (Allen et al., 2018; Miller et al
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of PhD), or Research Associate (more than 3 years of PhD). A strong preference is for individuals with (a) computer science or computer engineering degrees with previous experience in natural