Biomedical and Health Sciences

Build an agent-based B-cell model and test how prime-boost timing changes affinity maturation, then fit it to public serology time series.

Analyze NHANES data to test how ultra-processed food subgroups relate to CRP and WBC, while building causal inference and regression skills.

Compare how exercise and sleep loss change salivary IgA, and build a simple crossover study with clear controls and basic stats.

Learn how to rank cardiomyopathy variants with ancestry frequency, clinical labels, and protein-impact scores from public databases.

Build a model that separates stroke mimics from true strokes using public CT and MRI data, then check calibration so predictions mean something.

Audit clinical prediction models for bias with NHANES data, then test recalibration methods that improve fairness and prediction accuracy.

Measure how similar whole-grain breads can affect glucose differently, then analyze your crossover data with smart portion control and Bayesian methods.