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DTSTART;TZID=UTC:20190128T160000
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SUMMARY:Graduate Studies in Computational & Data Sciences Info Session - Central Campus
DESCRIPTION:Learn about graduate programs that will prepare you for success in computationally intensive fields — pizza and pop provided \n\nThe Ph.D. in Scientific Computing is open to all Ph.D. students who will make extensive use of large-scale computation\, computational methods\, or algorithms for advanced computer architectures in their studies. It is a joint degree program\, with students earning a Ph.D. from their current departments\, “… and Scientific Computing” — for example\, “Ph.D. in Aerospace Engineering and Scientific Computing.”\nThe Graduate Certificate in Computational Discovery and Engineering trains graduate students in computationally intensive research so they can excel in interdisciplinary HPC-focused research and product development environments. The certificate is open to all students currently pursuing Master’s or Ph.D. degrees at the University of Michigan.\nThe Graduate Certificate in Data Science is focused on developing core proficiencies in data analytics:\n1) Modeling — Understanding of core data science principles\, assumptions and applications;\n2) Technology — Knowledge of basic protocols for data management\, processing\, computation\, information extraction\, and visualization;\n3) Practice — Hands-on experience with real data\, modeling tools\, and technology resources.\nThe Graduate Certificate in Computational Neuroscience provides training in interdisciplinary computational neuroscience to graduate students in experimental neuroscience programs and to graduate students in quantitative science programs\, such as physics\, biophysics\, mathematics and engineering. The curriculum includes required core computational neuroscience courses and coursework outside of the student’s home department research focus\, i.e. quantitative coursework for students in experimental programs\, and neuroscience coursework for students in quantitative programs.
URL:https://micde.umich.edu/event/graduate-studies-in-computational-data-sciences-info-session-central-campus-f2018-2/
LOCATION:Weiser Hall\, 10th Floor\, 500 Church Street\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Info Session
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DTSTART;TZID=UTC:20180925T163000
DTEND;TZID=UTC:20180925T173000
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SUMMARY:Graduate Studies in Computational & Data Sciences Info Session - Central Campus
DESCRIPTION:Learn about graduate programs that will prepare you for success in computationally intensive fields — pizza and pop provided \n\nThe Ph.D. in Scientific Computing is open to all Ph.D. students who will make extensive use of large-scale computation\, computational methods\, or algorithms for advanced computer architectures in their studies. It is a joint degree program\, with students earning a Ph.D. from their current departments\, “… and Scientific Computing” — for example\, “Ph.D. in Aerospace Engineering and Scientific Computing.”\nThe Graduate Certificate in Computational Discovery and Engineering trains graduate students in computationally intensive research so they can excel in interdisciplinary HPC-focused research and product development environments. The certificate is open to all students currently pursuing Master’s or Ph.D. degrees at the University of Michigan.\nThe Graduate Certificate in Data Science is focused on developing core proficiencies in data analytics:\n1) Modeling — Understanding of core data science principles\, assumptions and applications;\n2) Technology — Knowledge of basic protocols for data management\, processing\, computation\, information extraction\, and visualization;\n3) Practice — Hands-on experience with real data\, modeling tools\, and technology resources.
URL:https://micde.umich.edu/event/graduate-studies-in-computational-data-sciences-info-session-central-campus-f2018/
LOCATION:Weiser Hall\, 10th Floor\, 500 Church Street\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Info Session
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DTSTART;TZID=America/Detroit:20180913T090000
DTEND;TZID=America/Detroit:20180913T140000
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SUMMARY:Data-Intensive Social Science Challenge Symposium
DESCRIPTION:Data-intensive social science is one of the research focus areas that MIDAS supports with its Challenge Awards. Our long-term goal is to support this research area more broadly\, using the Challenge Award projects as the starting point to build a critical mass. This symposium offers a platform for all participants to explore collaboration opportunities and aims to attract more researchers to our hub. The two Challenge Award teams will give in-depth presentations\, and all participants are encouraged to submit posters on research related to data-intensive social science. \nRegistration | Poster submission form (Due Monday\, Sept. 10) \nPreliminary Schedule: \n9 am: Introduction \n9:05 am to 11:35 pm: Challenge Award presentations \n\nComputational Approaches for the Construction of Macroeconomic Data\, Matthew Shapiro and team\nA Social Science Collaboration for Research on Communication and Learning Based upon Big Data\, Michael Traugott and the UM-Georgetown team\n\n11:35 am to 1 pm: lunch\, poster session and networking (Please fill out this form to submit a poster; deadline is Monday\, September 10) \n1 to 2 pm: Panel discussion: the future of data-intensive social science research at U-M \n\nMartha Bailey\, Professor\, Economics\, University of Michigan\nSara Heller\, Assistant Professor\, Economics\, University of Michigan\nMatt Shapiro\, Professor\, Economics\, University of Michigan\nLisa Singh\, Professor\, Computer Science\, Georgetown University\nMike Traugott\, Professor Emeritus\, Communication Studies\, Political Science\, University of Michigan
URL:https://micde.umich.edu/event/data-intensive-social-science-challenge-symposium/
LOCATION:Weiser Hall\, 10th Floor\, 500 Church Street\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Conference
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