Curriculum
The T32 Training Curriculum aligns closely with that of the larger Bioinformatics Data Science Doctoral Program, while placing additional emphasis on professional development. The degree requires a minimum of 43 credits. Degree requirements are outlined in the CBB T32 Program of Study and students are required to maintain an updated version of the document.
The T32 Training Curriculum is composed of three components:
Scientific Curriculum
Students are required to take 18 credits of scientific courses related to Bioinformatics Data Science, including 4 core courses and 2 electives. Bioinformatics Data Science courses (BINF) are shown with syllabi on this page.
Development Curriculum
Students must take 9 credits of courses to help develop skills in leadership, communication, and teamwork. This includes an Ethics & Team Science course, an Internship, and presenting in the weekly program Seminar. Ethics & Team Science was developed specifically for the T32 program and addresses topics of Ethics, Collaboration, RCR, and much more.
BINF667-017: Ethics & Team Science
Instructors: Thomas Powers, Abhyudai Singh, Ryan Zurakowski,
Credits: 3
Ethics in Data Science and AI* – Dr. Powers
Description: This seminar will provide participation- and case-based ethics education to evaluate the ethical, social and policy impacts of data gathering, automated analysis, and applications in fields ranging from healthcare, public safety, and agriculture to homeland security, e-commerce, and the biological and environmental sciences.
*Students in Ethics & Team Science take first third of Ethics in Data Science and AI (PHIL655)
Responsible Conduct of Research and Rigor & Reproducibility – Dr. Singh
Description: Covers the topics of responsible conduct of research, scientific rigor and reproducibility, ethics, diversity and equity. The course addresses: authorship and ownership, the sanctity of data (fabrication and falsification), data sharing, peer review, conflicts of interest, whistle-blowing: benefits and risks, mentor-trainee responsibilities, and collaborative science.
Interdisciplinary Research Practice – Dr. Zurakowski
Description: In this portion of the course, students will work as a group, and will develop an interdisciplinary mock research plan to address a topic proposed by either a program-affiliated faculty member or an industry partner. We will use this mock research plan to develop and discuss “soft” materials including cold e-mails to collaborators, Publication and Authorship Agreements, Communication and Collaboration Scheduling, Consortium and Contractual Agreements, Multiple PI/PD leadership plans, and Conflict Resolution. Lectures and discussions will focus on how to approach potential new collaborators, how to successfully communicate across different disciplines, how to manage communication, budgeting, and scheduling for multi-site projects, potential sources of conflict and how to preemptively avoid them when possible, and how to handle conflict effectively when it arises.
Research & Dissertation
Students are required to complete 6 credits of Research and 9 credits of Doctoral Dissertation.
Additional Requirements
CBB T32 Trainees must also complete Preliminary, Candidacy, and Dissertation Exams as outlined in the requirements for the Bioinformatics Data Science PhD.
Program Timeline
CBB T32 Trainees are expected to complete the Bioinformatics Data Science PhD program and its milestones in a timely manner. Students are expected to keep track of their requirements and schedule exams. A suggested program timeline consists of:
- BDS program core courses (Y1)
- Common T32 development curriculum (Y2)
- Internship (Y2-Y3)
- Cohort programs, team building, leadership (Y1-Y5)
