11 big-data-clustering-phd Postdoctoral positions at University of California, Merced
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of quantum wavefunctions. Some of the possible projects involve international collaborations. Available computational resources include two shared clusters at Merced, computing nodes dedicated to the group
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quantitative, qualitative, and mixed-methods analyses, employ multiple social scientific methods, often in conjunction, including data collection and statistical analysis of large-scale data, among other
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opportunity to work in interdisciplinary team at the interface of experiment, big data, and statistical learning. Responsibilities of this position will include: Develop high-throughput assays and validate
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wildtype fungal structures or culturing and growing them in the lab. Perform characterization tests including imaging, mechanical, and chemical testing and subsequent analysis. Analyze data to create
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requirements Curriculum Vitae - Your most recently updated C.V. Cover Letter Reference requirements 3-5 required (contact information only) a PhD. degree in Electrical or Mechanical Engineering Apply link
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Scholar position is currently open in Dr. Xiaoyi Lu’s PADSYS Lab, focusing on the exploration of high-performance and scalable systems for emerging scientific applications, real-time Big Data processing
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qualifications Candidates should have training or experience with biomedical optics and intravital imaging. Experience with optical system design, circuit design, and computer programming will be particularly
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Requirements Document requirements Curriculum Vitae - Your most recently updated C.V. Cover Letter Authorization of Information Release - As a condition of employment, the finalist will be required
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excellent opportunity to work in the development of external relationships and to engage in industry-university partnerships at the cutting edge of engineering, computer and data science, technology, natural
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experimental smart farm. This role will involve conducting experiments to evaluate the performance of the network in real-world agricultural settings, aiming to enhance efficiency, productivity, and data-driven