Year 1
1st year Medical School basic sciences curriculum. (Molecules and Cells, Immunology, Neuroscience, and Physiology). This program fulfills the biology curriculum, although students will usually want to take additional advanced seminars in neuroscience. These courses usually fill a student’s time during the first year and are supplemented with rotations.

Year 2 or Years 1 & 2 Electives in the Engineering and Physical Sciences
The following curriculum is to be completed in Year 2 if taking the SOM basic life sciences track or in Years 1-2 if taking the alternative track. Students are required to take at least 2 courses per semester in Year 2, with at least one of these being at the 600/700 level. Curricula are to be designed with the guidance of the student’s mentor. Suggested electives are given below for each track (choose 4 of 6 each semester). Qualifiers are taken either at the end of the second year or in the middle of the third year.

Year 3 (Choose 4 of following) and Year 4 (Choose 2 of following)

Applied Mathematics and Statistics 550.361 Linear Optimization 550.420 Introduction to Probability 550.426 Introduction to Stochastic Processes 550.430 Introduction to Statistics 550.434 Nonparametric and Robust Methods 550.437 Statistics, Information and Perception 550.620 Probability Theory I 550.621 Probability Theory II 550.626 Stochastic Processes II 550.630 Statistical Theory 550.631 Statistical Inference 550.632 Multivariate Statistical Theory 550.633 Time Series Analysis 550.634 Nonparametric and Robust Inference 550.661 Foundations of Optimization 550.662 Optimization Algorithms 550.672 Graph Theory 550.681 Numerical Analysis 550.692 Matrix Analysis and Linear Algebra 550.723 Markov Chains 550.730 Topics in Statistics: Statistical Pattern Recognition 550.764 Optimization of Functionals 550.790 Topics in Applied Mathematics: Deformation Analysis for Images and Shapes Mechanical Engineering 530.601 Continuum Mechanics 530.648 Group Theory in Engineering Design 530.669 Computational Methods of Engineering	Biomedical Engineering 580.473 Magnetic Resonance in Medicine 580.472 Medical Imaging Systems 580.744 Pattern Theory: From representation to Inference Electrical and Computer Engineering 520.414 Image Processing and Analysis I 520.415 Image Processing and Analysis II 520.432 Medical Imaging Systems 520.435 Digital Signal Processing 520.447 Introduction to Information Theory and Coding 520.497 Information Theory 520.608 Image Reconstruction and Restoration 520.614 Linear Systems Theory 520.630 Introduction to the Calculus of Variations and Optimal Control 520.643 Digital Multimedia Coding and Processing 520.644 Pattern Theory: From representation to Inference 520.645 Adaptive Filtering 520.646 Wavelets and Filter Banks 520.651 Random Signal Analysis 520.652 Filtering and Smoothing 520.674 Information Theoretic Methods in Statistics Bioethics Elective 306.655 Ethical Issues in Public Health	Computer Science 600.303 High Performance Computing 600.357 Computer Graphics 600.441 Vision-Based Interaction for Man and Machine 600.445 Computer-Integrated Surgery I 600.446 Computer-Integrated Surgery II 600.461 Computer Vision 600.462 Applications of Computer Vision 600.630 Advanced Topics in Physics-Based Computer Vision 600.646 Advanced Computer-Integrated Surgery 600.652 Advanced Computer-Integrated Surgery Seminar 600.746 Medical Image Analysis Seminar Mathematics 110.405 Analysis I 110.406 Analysis II 110.413 Introduction to Topology 110.417 Partial Differential Equations for Applications 110.423 Lie Groups 110.427 Introduction to Calculus of Variation 110.439 Introduction to Differential Geometry 110.605 Real Variables 110.619/110.620 Lie Groups and Lie Algebras 110.631/110.632 Partial Differential Equations 110.645/110.646 Riemannian Geometry