Introduction to Research and Research Communities in Physics
01:750:155:01
Fall 2025

Monday, 10:20 to 11:40am
ARC 333 (Busch)
Instructor: Alyson Brooks

Instructor Contact Info

Email: abrooks[at]physics.rutgers.edu
Office hours: TBD
Teaching Assistant's email: TBD
Teaching Assistant's office hours: TBD

Description

This is a 1.5 credit Pass/No-credit course introducing first year students to research and the research community in Physics & Astronomy. There are three components to the course: (i) introduction to coding in Python; (ii) a hands-on research project in a sub-field of Physics; and (iii) interactive professional development discussions.

No previous research or computing experience is assumed. We will start at the beginning!

Prerequisites: None. Registration requires special permission of Undergraduate Program Director, upd@physics.rutgers.edu

Course-Level Learning Goals

Foundational Coding Skills: Students will learn the fundamentals of coding in Python and the basics of data visualization.
Understanding of Research: Students will learn the framework of a research project via analysis on data to address a science question. Students will also learn how to create a final work product in the form of a figure, and work on science communication skills via presentation of their results.
Community Building and Professional Development Students will build their network within the Physics and Astronomy department via connections with peers, near peer mentors, graduate students, and faculty. Students will also develop skills that will help them succed in Physics and Astronomy, both during their undergraduate career at Rutgers and beyond.

Course Structure

There will be one 80-minute lectures per week in Allison Rd Classroom (ARC) 333 on Busch Campus. Attendance and active participation in class is required.

The first part of the course we’ll equip you with the skills you need to start working on an astro/physics research project. These skills include programming in Python, and critical reading and writing of science literature. No previous research or computing experience is assumed.
Computer Programming: Introduction to working in a UNIX-based environment, and introduction to programming in Python. Many of the lessons will be asynchronous, leaving class time open for active coding of assignments with support from the instructor and TA.
Understanding Science and Reading Scientific Papers: We will build up to reading peer-reviewed articles in scientific journals. Through these readings we will become familiar with the methods and results of some recently published research.

The second part of the course will be guided research with your research mentor and your class partner(s).
Research Projects:>There are several projects proposed by Rutgers Physics and Astronomy faculty, postdocs, and graduate students. You will rank the projects that interest you most, and will be assigned to projects in teams of two (three if necessary). Examples of past project descriptions can be found here. Your research mentor will lead one-on-one, hands-on lessons for you and your partner(s) throughout the second half of the semester.
Research Presentations:One of your most important roles as a scientist is to communicate your research to your colleagues and the broader public. At the end of the semester, each research team will give a 5-minute presentation to research collaborators and mentors, which will also be open to the Physics and Astronomy Department. You will receive public speaking training in class.

The third part of the course (interweaved with the other two) will be focused on professional development and how to build experiences that make you competitive for different undergraduate opportunities.
Professional Development: We will cover a variety of topics, including career paths in physics and astronomy, learning strategies, Rutgers resources, speaking skills, and how to find and apply for internships. This will give you a head start on pursuing opportunities after the semester is over.

Schedule: Topics and Assignments

This syllabus may be modified as the semester progresses.

Social events will be scheduled throughout the semester. We will schedule these soon and update the calendar accordingly.

Week
Topics
Due
Sept 8 Introduction to the seminar  
Sept 15 Learning Strategies and RU resources;
reading a popular science article
Writing assignment #1;
Meet with TA
Sept 22 Intro to Unix and text editors Unix exercises
Sept 29 Intro to Python: notebooks/numpy Coding assignment #1
Oct 6 Research project pitches Ranked project choices
Oct 13 Python coding, cont'd: loops and functions Meeting with TA;
Coding assignment #2
Oct 20 Python cont'd: plotting Coding assignment #3;
Meet with project mentor(s)
Oct 27 Internships, REUs, etc Writing assignment #2;
Meet with project mentor(s)
Nov 3 Research projects Read/discuss relevant paper with mentor
Nov 10 Research projects Develop elevator pitch for project
Nov 17 Research projects Write Intro slides for research talk
Nov 24 Research projects; How to give a talk Methodology slides preparation
Dec 1 Navigating RU; UPD; career services Research; slide preparation
Dec 8 Final presentations to department  

 

Teaching Assistant

The course will have a graduate Teaching Assistant (TA). The TA is an additional resource for students to use throughout the entire academic year (yes, even after the seminar ends), and maybe even beyond. The TA is available to guide students on homework, research, selecting courses, and in-class assignments. The TA will be present at the in-class exercises. The TA is around to help with anything students may want to talk about. In fact, students will be required to periodically meet with the TA to guarantee that they take advantage of this excellent resource!

Grading Policies

The seminars is credit/no credit. To receive credit for the seminar, students are expected to participate. Every writing and coding assignment will be graded on a 10 and 20 point scale, respectively. To receive credit for the seminar, students are expected to achieve 70% of the points. Additionally, students must participate in the final research project and presentation, or they will not receive credit for the seminar. Finally, the seminar requires that students not miss more than three classes. Missing more than three classes will result in no credit. If you expect to miss a class, please use the University absence reporting website to indicate the date and reason for your absence. An email is automatically sent to me.

Late homework: Seek arrangement with the instructor at least 24 hours in advance if you think you have a legitimate excuse for late work.

Re-grades: You will be allowed to make corrections to any mistakes on the coding assignments and have it regraded.

Assignments

All assignments will be found under the "Modules" link from our Canvas course site, and you will be required to submit your completed assignments through Canvas as well.

Please note that for each writing assignment, I will require the use of turnitin, which will scan your document for signs of plagiarism (which is never allowed). When your writing assignments ask you to answer straightforward questions about reading assignments, please do your best to answer the questions using your own words and explanations. Students will be held to the Rutgers policy on academic integrity.

Coding assignments are meant to be straightforward practice of what we have learned in class. All assignments come from the online resource "Learn Python The Hard Way" (LPTHW). To complete an assignment, please create a new Jupyter notebook in your home directory when you are logged in to the class server.

Course Materials

There is no textbook for this seminar, but you should expect to take notes. Note that access to a computer outside of the classroom time is also required. We are happy to help identify resources if access to computing is an issue.

The Python lessons will be taught from instructional iPython Notebooks which will be found in Canvas.

There are also many freely available textbooks on programming in Python, which you could optionally use for Python help (no readings will be assigned from these books). Take a look at this webpage's free Python texts labeled "beginner" for supplemental texts that might be useful programming references appropriate for this course. Three reference texts that I recommend include Learn Python the Hard Way (which isn't actually hard!), A Byte of Python, and A Whirlwind Tour of Python.

Resources

Here are some web resources you may find illuminating or indispensable:

Students with disabilities should consult the department policy.

Disability Services
(848) 445-6800 / Lucy Stone Hall, Suite A145, Livingston Campus, 54 Joyce Kilmer Avenue, Piscataway, NJ 08854
Rutgers University welcomes students with disabilities into all of the University's educational programs. In order to receive consideration for reasonable accommodations, a student with a disability must contact the appropriate disability services office at the campus where you are officially enrolled, participate in an intake interview, and provide documentation. If the documentation supports your request for reasonable accommodations, your campus’s disability services office will provide you with a Letter of Accommodations. Share this letter with your instructors and discuss the accommodations with them as early in your courses as possible. To begin this process, please complete the Registration form on the ODS web site.

Just In Case Web App
Access helpful mental health information and resources for yourself or a friend in a mental health crisis on your smartphone or tablet and easily contact CAPS or RUPD.

Counseling, ADAP & Psychiatric Services (CAPS)
(848) 932-7884 / 17 Senior Street, New Brunswick, NJ 08901
CAPS is a University mental health support service that includes counseling, alcohol and other drug assistance, and psychiatric services staffed by a team of professional within Rutgers Health services to support students’ efforts to succeed at Rutgers University. CAPS offers a variety of services that include: individual therapy, group therapy and workshops, crisis intervention, referral to specialists in the community and consultation and collaboration with campus partners.

Violence Prevention & Victim Assistance (VPVA)
(848) 932-1181 / 3 Bartlett Street, New Brunswick, NJ 08901
The Office for Violence Prevention and Victim Assistance provides confidential crisis intervention, counseling and advocacy for victims of sexual and relationship violence and stalking to students, staff and faculty. To reach staff during office hours when the university is open or to reach an advocate after hours, call 848-932-1181.

Scarlet Listeners
(732) 247-5555
Free and confidential peer counseling and referral hotline, providing a comforting and supportive safe space.

Astrophysics at RutgersDepartment of Physics and AstronomyRutgers University

Last updated: Mar 27, 2024 by Alyson Brooks