Degrees and Tracks
Your Options As a Physics Major
The track options listed below allow students to specialize their B.S. degree in a particular area. This specialization is noted on the student’s transcript, so potential employers or graduate schools clearly see the area of specialization that has been chosen. The tracks are optional, and each track specifies a sub-set of the required technical electives so that students gain expertise in the designated area. Students may only complete one track.
B.S. in Physics
The Bachelor of Science degree in Physics
- The most-conferred undergraduate physics degree
- Preparation for any scientific or technical career path, including graduate studies in Physics
- Students may opt to pursue a specialized track
Students seeking a B.S. in Physics may choose from 5 different Physics tracks, or may elect not to pursue a degree track. Students who pursue a track must still complete the core requirements of the B.S. degree, however each of these tracks specificies how students fulfill many of the technical electives of the B.S. in Physics.
Tracks for B.S. in Physics
- Preparation for graduate studies in physics or related fields
- Maximum flexibility in selection of technical electives
- Preparation for direct entry into technical careers in industrial or government research or development laboratories or for graduate studies in physics or related fields
- Flexible elective selection that includes courses in computational science, as well as applied physics and engineering, with an emphasize on laboratory skills, and undergraduate research
- Preparation for graduate studies in astronomy or astrophysics or directly entering research or technical positions in these areas
- Courses in astrophysics, and undergraduate research
Biological Physics Track
- Preparation for graduate studies or professional degrees in biological or medical physics or careers in the health professions
- Allows for completion of common pre-med requirements, for students interested in medical school
- Courses in biological physics, biology, chemistry
Chemical Physics Track
- Preparation for research careers or graduate studies at the interface between Physics and Chemistry or Physics, Chemistry, and Biology as well as the health professions
- Flexible elective selection that includes courses in chemistry
Computational Physics Track
- Preparation for graduate studies or direct entry to the workforce in technical fields such as computational physics, data science, software engineering
- Courses in computer science as well as computational and numerical techniques in Physics, training in parallel computation and remote computing using Pittsburgh Supercomputer Center resources
Alternative Degree Options
B.A. in Physics
- Fewer mathematical and technical requirements than the B.S.
- Allows the combination of Physics with work in non-technical areas
- May be combined with a minor or double major in Colleges of Humanities and Social Science or Fine Arts, etc.
Double Majors / Double Degrees
Students have the option to pursue a double major or multiple degrees combining Physics with another discipline. These options require advanced planning, but many can be accomplished in four years by energetic and dedicated students. Interested students should consult with the Director of Undergraduate Affairs to discuss their options.
Minor in Physics
Students seeking to strengthen their background in areas outside physics may also opt to pursue a minor as part of their undergraduate studies. Most Carnegie Mellon departments offer a minor in their disciplines and interested students should see the current Undergraduate Catalog for details.
A selection of common technical minors is listed below:
- Minors offered by the Mellon College of Science
- Biological Science
- Environmental and Sustainability Studies
- Mathematical Sciences
- Scientific Computing
- Minors offered by the Carnegie Institute of Technology
- Biomedical Engineering
- Engineering Studies
- Technology and Policy
- Minors offered School of Computer Science
- Computer Science
- Machine Learning