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Remote Online Sessions for Emerging Seismologists 2021 (ROSES)

ROSES 2021 was designed to have both synchronous and asynchronous course enrollment options to accommodate students across multiple time zones. Each week had a single course session containing a live, hour-long lecture component, where a field expert presented a lecture or information about an important aspect of seismology. This lecture was moderated and allowed participant questions. This was then followed by a live 'laboratory' session, where this instructor would demonstrate and execute code that built upon and applied the topics discussed in that day's lecture. This code was made available to all students, who would work through it simultaneously and use the code to tackle problems the instructor would provide. A slack channel for each lecture allowed students to debug and share their code together and consult the instructors for clarifications or general questions about the course materials. ROSES 2021 also took advantage of the Slack channel to build community across a geographically diverse student cohort.

Topics focus on a combination of novel and upcoming topics in seismology, and topics that are useful for seismology students but may not be formally available via coursework at a university. You can view and run the course materials online by clicking on the badge below:

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Contact

ROSES 2021 is co-organized by Fransiska Dannemann Dugick, Liam Toney, Nate Stevens, Sydney Dybing and Anant Hariharan and advised by Suzan van der Lee, American Geophysical Union (AGU) Seismology Section president. Please direct any questions to [email protected].

Authorship

Individual unit lectures and data exercises are produced by the respective instructor. This GitHub repository is maintained by Fransiska Dannemann Dugick with assistance from the ROSES 2021 instructor and organizer team. DOI

Acknowledgements

ROSES 2021 is generously supported by the Seismological Society of America, the Incorporated Research Institutions for Seismology, the AGU Seismology Section, and the Alaska Satellite Facility at the University of Alaska Fairbanks.

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  • Jupyter Notebook 92.1%
  • Python 7.9%