Edward A. Knapp Undergraduate Fellowship

June 7 - August 15, 2015 -

Program Overview

The ability to mathematically model complex systems has become a prerequisite to successful science in any field. Writing a simulation is not enough; career scientists today should be able to analyze results, recognize statistical regularities, formulate conjectures, and pursue possible proofs about why these conjectures are true. This hands-on summer program will give you a toolbox for understanding and using mathematical modeling in complex systems and your discipline. The Santa Fe Institute’s Edward A. Knapp Undergraduate Fellowship uses an integrated approach. The program is transdisciplinary, with problems, methods, and data sets drawn from across science. You will move back and forth freely along a spectrum of methods learning how to:

- Design a mathematical model of a physical, biological or social system
- Identify opportunities to solve this model exactly or approximately
- Code and run simulations of the model
- Analyze your simulations’ running time and memory use to improve
their efficiency
- Test results against theoretical predictions and real-world data sets
- Formulate new conjectures based on your results and try to prove or
disprove them

This program is of special interest to you if you’re from computer science (CS), pure and applied mathematics, and physics, and we also welcome applicants from chemistry, quantitative biology, and social science. We aim to build your capacity for computational and mathematical modeling, and train you within a group who will support each other in building a wide range of skills. For example, CS students can help mathematics students with their programming, mathematics students can help physics and CS students with their theoretical analyses, and biology or social science students can help others to ground their models in reality. We want you to recognize that what may be easy for you can be intimidating to others and vice versa; we want to help you build knowledge collaboratively to become fearless about learning new skills and acquiring tools and techniques beyond your current comfort zone. If you are looking for a chance to do independent research, we encourage you to apply — especially if you are a highly talented student who attends an institution with limited research opportunities. Women and minorities are especially encouraged to apply. Your main work will be a small-group research project working with SFI mentors. Prior to your SFI residency you will be encouraged to complete SFI’s MOOC “Introduction to Complexity.” You will also attend part of SFI’s flagship Complex Systems Summer School and attend tutorials on the basics of data analysis, including concepts from computation, linear algebra, and statistics throughout the summer. For more information about logistics and the schedule please visit our wiki. Learn more about the 2014 REU cohort and watch videos of their final presentations here! Participants are expected to be in residence in Santa Fe for approximately 10 weeks, from June 7 to August 15, 2015.

Program Leader

Cristopher Moore, is a SFI Professor and formerly a Professor at UNM, Albuquerque, where he held a joint appointment in CS and Physics. Moore maintains an adjunct position at UNM and is active in graduate student advising. He is a regular lecturer in SFI’s Complex Systems Summer School, and is frequently invited to speak on the connections between CS and physics. Moore is co-author (with Stephan Mertens) of The Nature of Computation, a wide-ranging textbook on theoretical computer science and its connections with physics. He has mentored REUs in most of the past 10 years, often leading to publishable work and successful graduate careers. Additional mentors in this program include a wide range SFI resident scholars.

Support

Housing and a meal plan will be provided, at no cost to the student, in single-occupancy rooms with shared bathrooms at St. John's College in Santa Fe. Modest living stipends will also be provided to interns during their stay, along with some support of round-trip travel expenses from the home institution. Because Santa Fe lacks a full public transportation system, we encourage those interns who can bring their private transportation to do so.

Eligibility

For the purposes of this program, an undergraduate student is one who is enrolled in a degree program (part-time or full-time) leading to a bachelor's degree. Students transferring from one institution to another who are enrolled at neither institution during the intervening summer may participate. College seniors graduating in Spring 2015 are not eligible; nor are graduating high school students who have not yet enrolled as undergraduates. Strong mathematical skills and experience with a programming language are favorably considered. Students from all backgrounds in the physical, natural, and social sciences are invited to participate. Applicants must be U.S. citizens or permanent residents. Women and minority students are encouraged to apply.

Application Requirements

- Current Resume (CV).
- Statement of your current research interests and what you intend to
accomplish during your internship (suggested length one to two pages).
- Two (2) letters of recommendation from scholars who know your work.
- Official transcripts from each college or university attended. Be sure to
request your transcripts from the registrar sufficiently in advance so
that we receive these records by the February 7 deadline.

To Apply

We will be accepting applications from December 2, 2014 to February 7, 2015 at www.santafe.edu. Applicants will be notified by e-mail in late February regarding the status of their applications. Official, sealed transcripts should be mailed to: Santa Fe Institute - REU Program , 1399 Hyde Park Rd., Santa Fe, NM 87501 Or emailed to education@santafe.edu For further information about the program, please e-mail Juniper Lovato at education@santafe.edu, or call (505) 946-2726. The Santa Fe Institute REU Program is supported by the National Science Foundation under Grant Number ACI-1358567 Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation

Skills :

Systems Biology

Additional Info:

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