Basic Coursework

3 credits of coursework in each of these three areas are required. CMB students can take any of a variety of graduate-level courses at the University to fulfill each of these subject requirements. The specific courses elected to fulfill these requirements are based on student's prior background and research interests to individualize coursework selections.

Additionally, Pharm 502 is required (grant writing), and 6 credits of elective courses are required. One of these courses must include a quantitative subject. Finally, continued participation in CMB student seminar course (CMB 850) and participation in a minimum of 4 CMB short courses (CMB 630) is required.

Students choose 6 elective credits from a wide array of available graduate courses. Courses offered by PIBS programs are listed in the PIBS Curriculum Guide. Other University courses may be taken according to each student's interests.

For MSTP fellows, CMB recognizes the contribution of some medical school coursework to their graduate education and individualizes their curricula accordingly.

PIBS 503: Responsible Conduct of Research (RCR). This course is specifically designed for graduate students in biomedical sciences and includes lecture material with sample cases covering each of several broad major areas, including: data collection, storage and ownership, animal and human subjects, scientific misconduct, conflict of interest, women, minorities, and cross-cultural issues in science, and gene and drug patents.

PIBS 504: Rigor & Reproducibility (R&R). The content of the course covers 4 main NIH-suggested areas: 1) Transparency in Research; 2) Blinding and Randomization, 3) Biological and Technical Replicates, and 4) Sample size, Outliers and Exclusion Criteria. For each of these areas, participants watch the NIH-produced videos (about 5 minutes each) with scenarios depicting common issues in these areas, read the “Discussion Material” and participate in a discussion about each video. Additionally, the instructor leads a discussion on data presentation, sex as a biological variable, reagent verification, and common statistical tests.