Medical Image Analysis Research
The Biomedical Image Analysis Group (BIAG) within the department of computer science offers various research opportunities for undergraduate students. We focus on designing algorithms to extract quantitative measures from biomedical data, in particular, from images (e.g., from computed tomography, magnetic resonance, or microscopy images). Many of our current projects make use of modern machine learning approaches. Our work is highly interdisciplinary and typically includes collaborators from the medical school and often from statistics, biostatistics, or applied mathematics. Current undergraduate research opportunities include, but are not limited to a) image analysis approaches for knee osteoarthritis, b) image analysis for breast cancer research, and c) image and shape analysis for the quantification of pediatric airways. Position types (credit, payment, volunteer) are flexible, but depend on the specific project. Strong programming skills are required, ideally in Python (as we mostly work with pyTorch these days). Knowledge of linear algebra, multivariate calculus, and basic knowledge of statistics would be useful. To apply, email Professor Niethammer (email@example.com) a brief statement of interest, a copy of your transcript, and, if possible, a brief CV.