The biomedical engineering program at the University of South Carolina allows students
to study and perform interdisciplinary research with faculty from the College of Engineering
and Computing as well as the USC College of Arts and Sciences and the USC Medical
B.S. (Bachelor of Science) - Biomedical Engineering
Our 130 semester-hour undergraduate program leads to the bachelor of science degree.
In this program you will explore wide-ranging biomedical topics including biomechanics,
biomaterials and tissue engineering. Our B.S. program prepares you for a career in
healthcare industry, as well as graduate and medical school.
M.E. (Master of Engineering) - Biomedical Engineering
Our 30 semester-hour M.E. degree program offers intensive, focused training in the
professional practice of biomedical engineering. The program is specifically designed
for students who plan to pursue industrial careers, as a graduate degree could enhance
their job application, yield a higher starting salary, and enable rapid promotion
within many corporate structures.
M.S. (Master of Science) - Biomedical Engineering
Our 30 semester-hour program includes a thesis and serves traditional chemical and
mechanical engineers who wish to obtain advance training in biological areas, or science
majors who wish to receive quantitative training, to enhance their qualifications
for industry or medical practice.
Ph.D. - Biomedical Engineering
Our 60 semester-hour doctoral program prepares graduates of the program to meet the
growing demands for advanced level research, development, and entrepreneurial positions
in the biomedical industry. You will focus on specialized research to improve health
with a dissertation that leads to a Ph.D.
Dr. Valafar's group is seeking one highly motivated individual for a Graduate Research Assistant position
in the Department of Computer Science and Engineering; Center for Computational Biology
and Bioinformatics at the University of South Carolina College of Engineering and
Computing. Our laboratory is interested in developing a machine learning mechanism
that will detect when the user is smoking based on sensor information gathered from
mobile devices (smartphones or smartwatches). This mechanism will then be deployed
to monitor smoking behavior of participants as the means to develop better social
models with a final goal of assisting in cessation of smoking. The ideal candidate
should be motivated and independent individual who is eager to learn new concept while
working in a team environment. Additional skills that will be helpful for this position
consist of: familiarity with pattern recognition and classification techniques and
Matlab (or open source equivalent). In addition knowledge of Android/java programming
is desirable. or more information Please contact Dr. Valafar by email at firstname.lastname@example.org .
Our graduates work for companies ranging from Fortune 500 research firms to entrepreneurial
start-ups and governmental agencies. Our career counselors can help you with placement
and interview skills.
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