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. Required Qualifications: Doctoral degree (PhD) conferred by start date Demonstrated experience with analysis of large health databases Training and experience in machine learning and deep learning methods
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test planning, instrumentation (e.g., strain gauges, LVDTs, DIC), execution of large-scale tests, and data analysis. Solid understanding of structural behavior, failure mechanisms, and durability issues
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(SIPLab) at Heriot-Watt specializes in the design of advanced data science techniques with applications ranging from robotics to imaging and communication, in a large variety of fields including defence
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programmes that are constantly renewed in response to issues in society. Our faculty is large enough to make a difference nationally and internationally, yet small enough to offer personalised education. This
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, creative start-ups, big data, big ambitions, hands-on learning, and a whole lot of robots, CMU doesn’t imagine the future, we invent it. If you’re passionate about joining a community that challenges the
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-dimensional data. We are interested in both data-driven models as well as models built from synthetic data. Within privacy, we are interested in different types of privacy measures and models (differential and
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of the Principal Investigator (PI). Engage with PI and U01 investigators to conduct the aims of the research award. Conduct research using large-scale secondary data analysis. Assist PI in the calculation of novel
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sensing provides large-scale and consistent observations, in-situ data collection remains a vital component for ground-truthing, model calibration, and validation of automated monitoring. However
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are expected to work as a close-knit team together with three PhD students to create a mutually supportive research environment. Candidates must be enthusiastic about building and working in a large
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the development of computational methods for genetics, high-throughput omics data and causal discovery. Our interdisciplinary and international team is jointly located at DKFZ and EMBL Heidelberg, and