American Mathematical Society, Mathematics Research Communities

3 1157Program ID: MRC-HYPERNET [#1157]
Program Title: Models and Methods for Sparse (Hyper)Network Science: June 5-11, 2022
Program Location: Rhode Island, United States [map]
Application Deadline: (posted 2021/09/03, listed until 2022/03/01)
Program Description:    

About the Mathematics Research Communities:

Mathematics Research Communities (MRC), a program of the American Mathematical Society (AMS), nurtures early-career mathematicians--those who are close to finishing their doctorates or have recently finished--and provides them with opportunities to build social and collaborative networks through which they can inspire and sustain each other in their work.

The structured program is designed to engage and guide all participants as they start their career. For each topic, the program includes a one-week summer conference, a Special Session at the next Joint Mathematics Meetings, and a longitudinal study of early career mathematicians.

The 2022 summer conferences of the MRC will be held at Beaver Hollow Conference Center, Java Center, NY where participants can enjoy a private, distraction free environment conducive to research. Beaver Hollow is located in Western New York, 45 minutes from the Buffalo Niagara International Airport, one hour from Rochester or Niagara Falls.

Those accepted into this program will receive a flat rate transportation allowance for the summer conference, and will be partially supported for their participation in the Joint Mathematics Meetings which follow in January 2023.

ELIGIBILITY: Individuals within one to two years prior to the receipt of their PhDs, and up to five years after receipt of their PhDs, are welcome to apply.  Most of those supported by NSF funds to participate in the MRC program will be US-based, that is, employed by or a full-time student at a US institution at the time of the MRC summer conference. However, the terms of the grant allow for a limited number of individuals who are not US-based. A few international participants may be accepted. Depending on space and other factors, a small number of participant slots may be available for self-funders. Applicants wishing to be considered as possible self-funded participants should email ams-mrc@ams.org at the time they apply and state that intention. Self-funders must satisfy the same criteria for admission as those who receive grant support. Individuals who have once previously been an MRC participant will be considered for admission, and their applications must include a rationale for repeating. Please note that individuals cannot participate in the MRC program more than twice. Applications from individuals who have twice been MRC participants will not be considered. Women and underrepresented minorities are especially encouraged to apply.  All participants are expected to be active in the full MRC program.

For any program, fellowship, prize or award that has a maximum period of eligibility after receipt of the doctoral degree, the selection committee may use discretion in making exceptions to the limit on eligibility for candidates whose careers have been interrupted for reasons such as family or health. Therefore, an applicant who has had to slow down or temporarily stop his or her career for personal reasons may request to be considered for an extension in the amount of time after the PhD degree. Please send exception requests to ams-mrc@ams.org.


REQUIREMENTS:
  • Completed on-line application form
  • One (1) reference letter submitted by a professor or supervisor who knows the applicant and can address how the applicant will benefit from, and contribute to, the MRC program.

Applications will close at 11:59 p.m. Eastern Time on Tuesday, February 15, 2022. Note that all applicants will be notified of their status by May 1, 2022.

Week 2a: June 5-11, 2022 -Models and Methods for Sparse (Hyper)Network Science 

Organizers:
Sinan G. Aksoy, Pacific Northwest National Laboratory
Aric Hagberg, Los Alamos National Laboratory
Cliff Joslyn, Pacific Northwest National Laboratory
Bill Kay, Oak Ridge National Laboratory
Emilie Purvine, Pacific Northwest National Laboratory
Stephen J. Young, Pacific Northwest National Laboratory
Jennifer Webster, Pacific Northwest National Laboratory

Graph and hypergraph models are powerful tools for understanding the kinds of critical systems studied at the National Laboratories, including computer networks, critical infrastructure systems, systems biology, and social networks. This MRC will focus on developing models and analytical methods to enable data-driven exploration and analysis of such systems through the lens of graphs and hypergraphs by addressing several challenges. One such challenge we will address is developing rigorous sparse models that can reproduce with high probability known features of realistic data sets. Most existing random graph models either cannot capture the simultaneous sparsity and connectivity of real world data sets or they are too specialized to a single application and not generalizable. A concurrent challenge that we will address in the workshop is to generalize graph theoretic concepts to higher order hypergraphs, and develop native hypergraph analytical methods, without sacrificing computational tractability. To mimic the organization of research teams at Business, Industry, and Government (BIG) organizations we will strive to have interdisciplinary teams in which team members will have different strengths that come together to solve a problem. For example, some team members will be solving theoretical challenges while others implement algorithms efficiently. This workshop will also include interactive sessions on preparing for BIG careers.


Application Materials Required:
Submit the following item online at this website to complete your application:
And anything else requested in the program description.

Further Info:
http://www.ams.org/programs/research-communities/mrc-22
800-321-4267 x 4189
 
Electronic submission of reference letters is requested.
If this is not possible, contact ams-mrc@ams.org.

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