CURRICULUM
Students are required to take a minimum of 30 semester hours of coursework before admission to candidacy. After these required courses and rotations, that leaves a minimum of nine remaining course credits (usually three courses) for electives during the second (or third) year. There are a wide variety of informatics and biomedical science courses and programs at the University of Colorado campuses and our students have been very creative at taking advantage them to pursue specific biomedical and informatics interests.
Students are required to take 1 computational topic elective (typically 3 credits). Examples are listed below:
Machine and Deep Learning (BIOS 7747, BIOE 5020/5021, CU Denver CCSI 5930, 5931 , CU Boulder: CSCI 5622, 6622)
Longitudinal Data – BIOS 6629
Causal Analysis – BIOS 6641
Data Visualization – BIOS 7719
Network Analysis – CSCI 5352 (CU Boulder)
Natural Language Processing - CSCI 5832 (CU Boulder)
Multi-agent systems – CSCI 5423, 7000 (CU Boulder)
Machine Intelligence – CSCI 5822 (CU Boulder)
SPECIALIZATIONS
Students are also required to take 2 domain electives (typically 3 credits each) in one of the following tracks. The tracks were developed to provide structure for electives and reflect the breadth of expertise of our faculty and campus.
Note: With mentor and program director approval, students can also create a custom track outside of these four specializations.
The Bioinformatics specialization is focused on leveraging and integrating big molecular data (genetics, genomics, microbiome, metabolomics, proteomics) for insights into human biology and disease. Bioinformatics research involves the development of novel computational approaches that leverage methodology in data science, statistics, and machine learning, in addition to database and software skills, to fully harness the information in high-dimensional molecular data sets.
Example Options for Domain Electives: Selected Human Medical Genetics and Genomics (HMGP) courses, Selected Molecular Biology (MOLB) courses, Selected Biostatistics (BIOS) courses (e.g. BIOS 6655 Statistical Methods for Genetic Association, BIOS 7659 Statistical Methods in Genomics)
Clinical informatics is a subfield of biomedical informatics that focuses on the application of informatics in clinical settings to improve patient care and enhance healthcare processes. Its goal is to leverage data and technology to advance healthcare delivery and patient safety. Clinical informatics involves the use of artificial intelligence methods, information technology and data management to extract information from electronic health records, consumer health data, natural language, image and signal data, and self-management data. Extracted information is then used to implement decision support systems that provide data-driven recommendations for diagnosis and treatment and facilitate health information exchange to improve coordination of care across different healthcare organizations.
Example Options for Domain Electives: BIOS 6310: Practical Clinical Research Informatics, Selected Nursing (NURS) informatics courses (NURS 6284 Digital Tools for Connected Health, 6285 Human Computer Interaction Design Principles, 6279 Knowledge Management), selected Clinical Science (CLSC) courses (CLSC 6800 Introduction to Health Information Technology, 6820 Fundamentals of Health Information Technology Management). Selected CU Boulder courses (CSCI Human Computer Interaction).
Imaging informatics is a multidisciplinary field dedicated to analyzing and interpreting biomedical images to facilitate biological discovery, disease diagnosis, prognosis, and treatment planning. It focuses on the development and application of computational methods to process complex imaging data, using medical imaging, computer vision, and machine/deep learning algorithms.
Example Options for Domain Electives: CSCI 5931 Deep Learning, ELEC 5541 Advanced Deep Learning for Computer Vision, CU Boulder CSCI 5722 Computer Vision
The Computational Neuroscience specialization is focused on the use of computational approaches to understand the brain, including modeling of physical systems as well as statistical and data science techniques. Approaches to the former include ordinary differential equations and artificial intelligence as a model system; the latter includes the use of dimensionality reduction, time and frequency domain methods, and machine learning typically on large scale neurophysiology or behavior tracking data.
Example Options for Domain Electives: Selected Neuroscience (NRSC) course (NRSC 7501 Introduction to Neuroscience, NRSC 7612 Nervous System Modeling with NEURON, NRSC 7657 Workshop in Advanced Programming for Neuroscientists), Electrical Engineering (ELEC 5375 Engineering Neuroscience), Bioengineering courses (BIOE 5053 Optics and Microscopy) and CU Boulder courses (APPM 5370 Computational Neuroscience, ECEN 5811: Neural Signals and Functional Brain Imaging, ECEN 5831: Brains, Minds and Computers)
BIOMEDICAL SCIENCES "CORE" COURSES
This is a set of interdisciplinary courses required for first year graduate students enrolled in basic science Ph.D. programs at UCD|AMC. The objective of the courses is to provide the basic science information and introduction to the skills required for a successful research career in all disciplines of modern biomedical sciences. Topics cover the fundamentals of biochemistry, molecular biology, cell biology, developmental biology, molecular genetics, and biomolecular structure. Specialty topics required by individual programs are taken usually during the spring semester of the first year, and in some cases in the second year to round out the curriculum.
ACADEMIC PLANNING
1st Year Curriculum and Milestones
| Semester | Course | Title |
| Fall | BMSC 7806 | Foundations in Biomedical Sciences |
| Fall | CPBS 7601* | Computing Skills in the Biomedical Sciences |
| Fall | CPBS 7602* | Introduction to Big Data in the Biomedical Sciences |
| Fall | CPBS 7650 | Research Rotation #1 (required ~Sep.-Nov) |
| Spring | CPBS 7712 | Research Methods in Biomedical Informatics |
| Spring | CPBS 7650 Section 0V3 | Research Rotation #2 (required ~Jan.-March) |
| Spring | CPBS 7650 section 0V3 | Research Rotation #3 (required ~March-May) |
| Summer | CPBS 8990/ CPBS 7650 | Doctoral Thesis or Research Rotation #3 (if needed) |
Preliminary Examination (June)
Choose mentor (by mid-June)
* In 2024, we introduced two Core Topics specific to our program.
2nd Year Curriculum and Milestones
| Semester | Course | Title | Credits |
| Fall | BMSC 7820 | Statistics and Data Analyses for the Biomedical Sciences | 3 |
| Fall | Dept Varies | Elective Course** | 1-6 |
| Fall | CPBS 7650 Section 001 | Research | Varies |
| Fall | CPBS 7605 | Ethics (offered every other year | 1 |
| Spring | Dept Varies | Elective Course(s)** | 1-6 |
| Spring | CPBS 7650 Section 001 | Research | Varies |
| Summer | CPBS 8990 | Doctoral Thesis | 1 |
** See above for Elective Courses
Comprehensive Exam/Thesis Proposal
Years 3 - 5 Curriculum and Milestones
| Course | Title | Credits | |
| CPBS 8990 | Doctoral Thesis* | 5 credits/semester in fall & spring; 1 credit in summer |
Dissertation Committee meeting and Dissertation update talk –minimum of 1 per year; ideally 2 meetings per year each at ~ 6 month intervals.
Dissertation Defense (You must complete 30 credits of CPBS 8990 before or in the semester you defend)
Other Campuses
*Students who would like to take courses offered at another CU Campus, most commonly CU Boulder or CU Denver, must take the following steps, in this order:
- Email the course instructor to ask for approval to enroll as a student on a different campus
- Complete the Intercampus Enrollment Form, found on the CU Anschutz Registrar’s Website.
Email your completed Intercampus Enrollment Form to the PA, along with a copy of the email from the course instructor showing their approval for you to enroll in the course.