Translational Medical Science

Use root growth assays and calibration controls to screen emulsion safety, compare formulations, and build skills in dose response and statistics.

Mine PubMed and ClinicalTrials.gov to measure translation speed, compare therapy areas, and practice evidence-based data analysis for research.

Build text-mining and association analysis skills by linking clinical notes to drug-symptom signals and target hypotheses.

Build and test an adaptive utensil that reduces spill mass and feeding time, while learning wearable sensing, control logic, and human testing.

Build a pipeline that predicts ssDNA aptamers for α-synuclein fibrils and compares them with published winners using binding metrics.

Use generative chemistry and docking to design Hsp90 inhibitors, then test selectivity and ADMET filters with real compound data.

Test how loss, gain, and identity messages affect sunscreen reapplication, then connect behavior change to UV badge data and prevention outcomes.

Use GWAS summary stats to test whether vitamin D, omega-3, or magnesium may causally affect migraine risk, then rank one nutrient for follow-up.

Build a federated-learning model for acute kidney injury detection and measure how differential privacy changes accuracy, fairness, and data sharing.

Build a cheap gut transit model and compare ibuprofen and naproxen dissolution using smartphone colorimetry, pH, and fluid recipe changes.