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DTSTART:20070311T020000
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BEGIN:VEVENT
DTSTAMP:20260924T123309
DTSTART;TZID=America/Detroit:20260930T140000
DTEND;TZID=America/Detroit:20260930T150000
SUMMARY:Careers / Jobs:Internship Lab
DESCRIPTION:*RSVP required to attend. Click \"Join Event\" here:https://umich.joinhandshake.com/edu/events/1988560Are you ready to start searching for a great internship? Do you have a few ideas\, but you’re not sure where to get started? Let's talk about search strategy!! Get real-time\, personalized support by checking out Internship Lab. You’ll be guided by one of our Career Coaches who has designed thisexperience to provide you strategies\, tools\, and motivation to get on the right track with searching for internships. Chat with folks from the University Career Center to explore Handshake\, the University Career Alumni Network (UCAN) and to learn about other tools you can use to build a great job/internship search strategy. **If you're not sure what you're interested in\, consider making an \"Career Exploration and Planning\" appointment to get started clarifying your interests with a career coach in a 1-on-1 setting. Recent Grads: If you are an alumni\, you will not be able to access the link due the University’s policy of discontinuing alumni Zoom accounts 30 days after graduation. Please contact careercenter@umich.edu with the subject line “Recent Grad Help” to be set up with a 1:1. Include the name of the workshop/event in your email.We want to ensure full and equitable participation in our events. If an accessibility accommodation would promote your full participation in this event\, please indicate your accommodation requirements via the link below\, preferably at least 14 days prior to the program to ensure sufficient time for arranging your requested accommodation(s) or exploring suitable alternatives. If you have any questions regarding access to our programs\, please don't hesitate to reach out to Jocelyn Gaydos at jmgaydos@umich.edu. Accessibility accommodation form: https://forms.gle/FmFn35ZLxJ8kvPfSA  #UCC
UID:150032-21907885@events.umich.edu
URL:https://events.umich.edu/event/150032
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:
LOCATION:
CONTACT:
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BEGIN:VEVENT
DTSTAMP:20260924T172141
DTSTART;TZID=America/Detroit:20260930T140000
DTEND;TZID=America/Detroit:20260930T150000
SUMMARY:Workshop / Seminar:School of Public Health Program in the Environment
DESCRIPTION:
UID:149914-21907368@events.umich.edu
URL:https://events.umich.edu/event/149914
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Sessions
LOCATION:School of Public Health
CONTACT:
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BEGIN:VEVENT
DTSTAMP:20260918T140908
DTSTART;TZID=America/Detroit:20260930T143000
DTEND;TZID=America/Detroit:20260930T153000
SUMMARY:Presentation:Graduate Opportunities in Computational and Data Science information session
DESCRIPTION:The educational programs represented will be:\n\nPhD in Scientific Computing (MICDE)\nGraduate Certificate in Computational Discovery & Engineering (MICDE)\nGraduate Certificate in Computational Neuroscience (MICDE)\nGraduate Certificate in Data Science (MIDAS)\n\nThese add-on programs are open to U-M graduate students with an interest in scientific computing or data science. We will also discuss funding\, research\, and community opportunities. \n\nRefreshments will be provided. \n\nIf you have any questions about these programs or about the information session\, please reach out to MICDE (micde-contact@umich.edu) or MIDAS (midas-contact@umich.edu). \n\nNOTE: You are welcome to attend either session. We will hold two sessions in different locations\, but the content will be the same.
UID:152333-21913557@events.umich.edu
URL:https://events.umich.edu/event/152333
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Computation,Computational Medicine,Computational Modeling,Computational Science,Computational Social Science,Data Science,Engineering,Graduate,Graduate School,Graduate Students,Interdisciplinary,Micde,Michigan Engineering,Midas,Rackham,Research,Science,Scientific Computing,Sessions
LOCATION:3rd Floor, Johnson Rooms
CONTACT:
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BEGIN:VEVENT
DTSTAMP:20260922T115750
DTSTART;TZID=America/Detroit:20260930T153000
DTEND;TZID=America/Detroit:20260930T165000
SUMMARY:Workshop / Seminar:Algebraic Geometry Seminar: Crepant resolutions via stacks
DESCRIPTION:Consider an invariant that behaves nicely for smooth varieties\, such as Euler number\, Betti numbers\, or Hodge numbers. Suppose we want a version of this invariant for singular varieties that sees interesting information about the singularities. I will discuss how this naturally leads to the notion of crepant resolutions of singularities. However\, crepant resolutions (by varieties) are rare in practice. I will discuss joint work with M. Satriano in which we show that crepant resolutions actually exist in broad generality\, as long as one is willing to consider algebraic stacks. Specifically\, any variety with log-terminal singularities admits a crepant resolution by a smooth algebraic stack. As one consequence\, in joint work with J. Huang and M. Satriano\, we obtain a cohomological interpretation for Batyrev's stringy Hodge numbers. This talk will not assume familiarity with stacks.
UID:149657-21906898@events.umich.edu
URL:https://events.umich.edu/event/149657
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Mathematics
LOCATION:East Hall - 4096
CONTACT:
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BEGIN:VEVENT
DTSTAMP:20260924T111012
DTSTART;TZID=America/Detroit:20260930T160000
DTEND;TZID=America/Detroit:20260930T170000
SUMMARY:Workshop / Seminar:CCMB/DCMB Weekly Bioinformatics Seminar Series featuring Jianzhi Zhang\, PhD (Professor\, Ecology and Evolutionary Biology\, U-M)
DESCRIPTION:Jianzhi (George) Zhang is a Professor of Ecology and Evolutionary Biology interested in the relative roles of chance and necessity in evolution. He got his B. S. from Fudan University in Shanghai\, China\, and his Ph. D. in Genetics from Pennsylvania State University. He was a  Fogarty postdoctoral fellow at the National Institute of Allergy and Infectious Diseases before moving to the University of Michigan.\n\nAbstract\n\nAdaptive evolution proceeds through beneficial nucleotide substitutions in the genome\, yet the number of such substitutions (N) required to reach a local or global fitness peak where no single mutation further increases fitness remains unknown. Here we estimate N by simulating adaptive walks on two large\, complete\, multi-environment adaptive landscapes inferred from massive empirical data using machine learning\, with validation from smaller experimentally mapped landscapes. We find that N rises linearly with the number of variable sites (L) in the landscape\, regardless of prior adaptation in another environment. Extrapolation suggests a minimal N of 10^5 for typical prokaryotes and 10^7 for mammals. By contrast\, in highly rugged shuffled landscapes\, N is markedly reduced\, while fitness gains also shrink. The relatively smooth empirical landscapes therefore enable greater fitness gains while lengthening adaptive walks\, rendering even local fitness peaks effectively unreachable before environments change. These results explain the persistence of fitness gains in long-term evolution experiments and the widespread occurrence of beneficial mutations across species. They suggest that populations continuously adapt while remaining far from fitness optima\, challenging the long-held view that adaptation culminates at fitness peaks.
UID:150650-21909759@events.umich.edu
URL:https://events.umich.edu/event/150650
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Basic Science,Bioinformatics,Biology,Biosciences,Ecology,Genome
LOCATION:Medical Science Unit I - 4B700
CONTACT:
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