Research Experience for Undergraduates (Summer 2017) | Positions | Beckstein Lab

The Beckstein Lab offers a ten-week REU research program in computational biophysics for a highly motivated undergraduate student. The student will implement new algorithms for the analysis of biomolecular simulations in the MDAnalysis Python library and apply such algorithms to improve free energy calculations. She or he will be involved in contributing to a thriving and widely used open-source software project and learn to use state of the art approaches to rapidly develop fast code suitable for scientific work.

Students will receive a $5000 stipend plus an allowance for travel, on-campus housing and a meal plan for this ten-week program. The desired starting date is May 22, 2017 and end date is Jul 31, 2017. This full time research experience includes work in the lab with a faculty and PhD student mentor.

Application DEADLINE: May 5, 2017

The program is part of the SPIDAL project and funded through an NSF REU (Research Experience for Undergraduates) grant.

A successful candidate must be able to provide proof that they are eligible to work in the United States.

Questions

Please read this whole page first. If you have questions that remain un-answered:

• For general questions please use the contact form at the bottom of the page.
• For questions of a personal or confidential nature please email Dr Beckstein, oliver.beckstein@asu.edu.

Required qualifications

• Candidates must be enrolled in an undergraduate degree in Physics, Computer Science, Chemistry, Biology or related science.
• Your are enrolled in a full time degree program during 2017/2018 (i.e., you cannot do this REU at the end of your degree).
• They must demonstrate some experience with
  • using computation to solve a problem in physics, chemistry or biology or related areas and
  • a programming language

Desired qualifications

Demonstrated experience with

• Linux/UNIX,
• programming in Python/Cython (including parallel programming and programming on GPUs is a plus),
• contribution to open source software (provide a link to your GitHub or BitBucket profile if you have one)
• analysis of MD simulations (especially using the MDAnalysis library),
• use of a molecular dynamics simulation package such as Gromacs, NAMD, Amber or CHARMM.

How to apply

Submit the following by May 5, 2017:

1. CV
2. a 1-page essay describing your motivation, your qualification (how you meet the required and desired qualifications listed above), and how the research experience will benefit your future career
3. unofficial transcripts
4. one letter of reference

With identical qualifications, under-represented groups in STEM subjects will be preferentially selected.

Incomplete applications will receive low priority and may be ignored.

The application process is slightly different for ASU students and students from elsewhere in the US: follow the appropriate links:

• I am applying as a ASU student
• I am applying from another university in the U.S.

ASU Students

Apply through the job posting on the ASU website (you must be logged in with your ASURITE ID).

1. click Job Search in the top ribbon
2. click Search On-Campus Jobs
3. click Search openings
4. Enter Requisition ID and Search: 31681BR

Upload the application materials as a single PDF file in the order stated above. Your letter of reference may be sent separately but in your application you should say who is sending your letter of reference.

Students from elsewhere in the U.S.

If you are not at Arizona State University, please send the application materials as a single PDF file in the order stated above in a single email with subject REU Application to Dr Oliver Beckstein, oliver.beckstein@asu.edu.

Your letter of reference may be sent separately but in your application email you should say who is sending your letter of reference.

• Note that your travel to and from Phoenix within the lower 48 states is covered; for other travel arrangements please inquire by email.
• If you don’t live in the Phoenix area then you will be provided a room in student accommodation on campus within walking distance from the lab; you don’t have to make any arrangements.