Physics

Group of students in an active learning environment.

In this cohort of The Data Mine, students will experience an active research environment targeted at the analysis of large data sets from particle physics and astrophysics experiments. Students will be introduced to and employ a variety of tools and programming languages including Python. Research topics revolve around data from the CMS experiment on the Large Hadron Collider in Switzerland, the search for dark matter particles using the XENON experiment in Italy, and the new Vera Rubin telescope facility.


New Incoming students should apply for fall 2023 using the Purdue Learning Communities main application link.


Current Purdue students are able to apply for The Data Mine Physics Learning Community for 2023-24 from October 1, 2022 until March 31, 2023.

Eligibility

Open to any undergraduate student with an interest in the Data Sciences (first-year students and continuing students are both welcome)

Residential Component

  • New Incoming Students: Living in Data Mine residential space is required unless you are in the Honors College or have other special accommodations needed.
  • Returning Purdue Students: Data Mine housing for returning undergraduates has reached capacity for AY 2023-24.
  • Your roommate (in most cases) will be a member of The Data Mine.
  • If you want to live on campus, it is necessary to complete a housing contract. (Completing a housing contract is a separate process from applying for a learning community.)

Duration

Fall and Spring semesters

Required classes for students

The information below is subject to change.

Fall
  • PHYS 32300 (3 credits: lecture and lab) Research in Big Data I
  • TDM 10100, 20100, 30100, 40100 (1 credit; 4 sections available) The Data Mine I, III, V, VII
Spring
  • PHYS 32400 (3 credits: lecture and lab) Research in Big Data II
  • TDM 10200, 20200, 30200, 40200 (1 credit; 4 sections available) The Data Mine II, IV, VI, VIII

Events and Activities Included

  • Weekly dinners with Data Mine participants
  • Faculty and graduate student office hours onsite in Hillenbrand
  • Seminars by visiting speakers, including practicing data scientists
  • Social gatherings with Data Mine members
  • Meals with campus and community leaders
  • Game / recreation nights
  • Career and graduate school panels
  • Hackathons / data competitions
  • Professional development activities
  • Tour of Purdue's computational facilities