MSE Degree Requirements

To fulfill the requirements for the MSE degree, students must take 10 courses at the 5000 level or above. You may choose to write a thesis or complete the non-thesis degree. The two options differ only in the distribution of courses. Many students, especially those interested in research or later pursuing a PhD or MD, choose to write a thesis.

Required of All MSE Students

There are eight required course units that must be taken by students in both the thesis and non-thesis tracks. These are:

1 Math course (1 CU)

Math Courses for MS/PhD in Bioengineering

*Please note that not all courses will be offered every year/semester and it is up to the student to confirm they have the appropriate background for the course.

  • AMCS 6010 Algebraic Techniques for Applied Mathematics and Computational Science I
  • AMCS 6020 Algebraic Techniques for Applied Mathematics and Computational Science II
  • AMCS 6080 Analytic Techniques for Applied Math and Computational Science I
  • AMCS 6090 Analytic Techniques for Applied Mathematics and Computation Science II
  • BE 5040 Biological Data Science II: Data Mining Principles for Epigenomics
  • BE 5100 Biomechanics and Biotransport
  • BE 5160 High-performance Scientific Computing
  • BE 5180 Optical Microscopy
  • BE 5300 Theoretical and Computational Neuroscience
  • BE 5320  Computational Biophysics
  • BE/CIS 5370 – Biomedical Image Analysis
  • BE/CBE 5400 Principles of Molecular and Cellular Bioengineering
  • BE 5500 Continuum Tissue Mechanics
  • BE 5570 -Quantitative Principles of Drug Design
  • BE/CBE 5590 Multiscale Modeling of Biological Systems
  • BE 5660 Network Neuroscience
  • BE 5670 Mathematical Computation Methods for Modeling Biological Systems
  • BE 5840 Mathematics of Medical Imaging and Measurements
  • BIOL 5510 Statistics for Biologists
  • BIOL 5511 Biological Data Analysis
  • BIOL 5535 Introduction to Computational Biology & Biological Modeling
  • BIOL 5536 Fundamentals of Computational Biology
  • BIOL 5560 Advanced Statistics
  • BIOM 5200 Concepts and Methods in Biostatistics – Basic
  • BIOM 5210 Concepts and Methods in Biostatistics – Intermediate
  • BMIN 5020 Databases in Biomedical Research
  • BMIN 5030 Data Science for Biomedical Informatics
  • BMIN 5330, Statistics for Genomics and Biomedical Informatics
  • BSTA 6200 Probability I
  • BSTA 6210 Statistical Inference I
  • BSTA 6220 Statistical Inference II
  • BSTA 6300 Statistical Methods for Data Analysis I
  • BSTA 6510 Introduction to Linear Models and Generalized Linear Models.
  • BSTA 7510 Statistical Methods for Neuroimaging
  • BSTA 7740 Statistical Methods for Evaluating Diagnostic Tests
  • CBE 5080 Probability and Statistics for Biotechnology
  • CBE 5200 Modeling, Simulations, and Optimization of Chemical Processes
  • CBE 5220 Polymer Rheology and Processing
  • CBE 5250 Molecular Modeling
  • CBE 6170 Control of Nonlinear Systems
  • CHEM 5210 Statistical Mechanics 1
  • CIS 5150 Fundamentals of Linear Algebra and Optimization
  • CIS 5190 Applied Machine Learning
  • CIS 5200 Machine Learning
  • CIS 5360 Computational Biology
  • ENM 5020 Numerical Methods and Modeling
  • ENM 5030 Introduction to Probability and Statistics
  • ENM 5100 Foundations of Engineering Mathematics I
  • ENM 5110 Foundations of Engineering Mathematics II
  • ENM 5200 Theory and Computation for ODE/PED-constrained optimization
  • ENM 5200 Topics in Computational Science and Engineering
  • ENM 6000 Functional Analysis
  • ENM 6010 Special Topics in Engineering Mathematics – Nonlinear Dynamics and Chaos
  • ESE 5000 Linear Systems Theory
  • ESE 5020 Introduction to Spatial Analysis
  • ESE 5040 Intro to Linear, Nonlinear and Integer Optimization
  • ESE 5050 Control of Systems
  • ESE 5060 Introduction to Optimization
  • ESE 5300 Elements of Probability Theory and Random Processes
  • ESE 5310 Digital Signal Processing
  • ESE 5420 Statistics for Data Science
  • ESE 6030 Simulation Modeling and Analysis
  • ESE 6320 Random Process Models and Optimum Filtering
  • ESE 6740 Information Theory
  • GCB 5370 Advanced Computational Biology
  • MATH 5120/5140 Advanced Linear Algebra
  • MATH 5840 Mathematics of Medical Imaging
  • MATH 5861/BIOL 5860 Mathematical Modeling in Biology
  • MEAM 5220 Fundamentals of Sensor Technology
  • MEAM 5270 Finite Element Analysis
  • MEAM 5280 Advanced Kinematics
  • MSE 5150 – Mathematical Methods for Engineering Applications
  • STAT 5000 Applied Regression and Analysis of Variance
  • STAT 5010 Introduction to Nonparametric Methods and Log-linear Models
  • STAT 5030 Data Analytics and Statistical Computing
  • STAT 5100 Probability
  • STAT 5110 STATISTICAL INFERENCE
  • STAT 5120 Mathematical Statistics
  • STAT 5300 Probability
  • STAT 5410 Statistical Methods
  • STAT 5420 Bayesian Methods and Computation
  • STAT 5500 Mathematical Statistics
  • STAT 5710 Modern Data Mining
  • STAT 5810 Convex Optimization for Statistics and Data Science
  • STAT 7700/5030 Data Analytics and Statistical Computing
  • STAT 7760 Applied Probability Models in Marketing

1 Biological Science course

Biological Science Courses for MS/PhD in Bioengineering

*Please note that not all courses will be offered every year/semester and it is up to the student to confirm they have the appropriate background/prerequisites for the course.

*Please also note that there may be alternative courses that will meet the requirement, they should be 5000-level or greater and should generally be taught outside of SEAS.

  • BE 5260 Immunology for Bioengineers
  • BE 5270 Immune Engineering
  • BE 5300 Theoretical and Computational Neuroscience
  • BE 5400 Principles of Molecular and Cellular Bioengineering
  • BE 5530 Principles, Methods, and Applications of Tissue Engineering
  • BE 5540 Engineering Biotechnology
  • BE 5550 Nanoscale Systems Biology
  • BE 5580 Principles of Biol Fabrication
  • BE 5610 Musculoskeletal Biology & Bioengineering
  • BE 5650 Developmental Engineering of Tissues
  • BE 5660 Network Neuroscience
  • BE 5670 Modeling Biological Systems
  • BE 5690 Systems Biology of Cell Signaling and Behavior
  • BE 5760 The Cell as a Machine
  • BE 5780 – Principles of Controlled Release Systems
  • BIOL 5010 Advanced Cell Biology
  • BIOL 5062 – Biological Foundations for Bioengineering and Biotechnology: Cellular and Molecular Biology
  • BIOL 5110 Neural Systems and Behavior
  • BIOL 5116 Neural Circuits for Survival
  • BIOL 5210 Molecular Biology and Genetics
  • BIOL 5220 Human Evolutionary Genomics
  • BIOL 5231 Genome Science and Genomic Medicine
  • BIOL 5234 Epigenetics
  • BIOL 5240 Genetic Analysis
  • BIOL 5262 – Biological Foundations for Bioengineering and Biotechnology: Genomics and Omics Technologies
  • BIOL 5318 Systems Biology: Integrative physiology and biomechanics of the muscular system
  • BIOL 5825 Biochemistry and Molecular Genetics Superlab
  • BIOM 5010 Mechanisms of Disease and Therapeutics
  • BIOM 6000 Cell Biology
  • BIOM 5020 Mechanisms of Disease
  • BIOM 5100 Case Studies in Translational Research
  • BMB 5080 Molecular Biophysics I
  • BMB 5090 Macromolecular Biophysics II
  • BMB 5100 Data Analysis and Scientific Inference
  • BMB 5670 Bioinorganic Chemistry
  • BMB 5850/BBCB 5850 Wistar Institute Cancer Biology Course: Signaling Pathways in Cancer
  • BMB 5900 Biological Physics
  • BMB 6140 Membrane Structural Biology
  • BMB 6160 Medical Problems in Modern Biochemistry
  • BMB 6220 Physical Principles of Mechano-Enzymes
  • BMB 6240 Ion Channels and Pumps
  • BMB 6250 Optical Methods in Cell Physiology
  • BMB 6260 Mass Spectrometry and Proteomics
  • BMIN 5010 Introduction to Biomedical and Health Informatics
  • BSTA 5090 Introduction to Epidemiology
  • BSTA 5100 Introduction to Anatomy and Physiology
  • BSTA 7510 Statistical Methods for Neuroimaging
  • CAMB 5110 Principles of Development
  • CAMB 5220 Human Evolutionary Genomics
  • CAMB 5260 Experimental Principles in Cell and Molecular Biology
  • CAMB 5320 Human Physiology
  • CAMB 5500 Genetic Principles
  • CAMB 5970 Neural Development, Regeneration and Repair
  • CAMB 6090 Vaccines and Immunization Therapy
  • CAMB 6100 Molecular Basis of Gene Therapy
  • CAMB 6330 Advanced Seminar in Gene Therapy
  • CAMB 6380 Advanced Seminar in Cell Death and Survival
  • CAMB 6920 Advanced Topics in Cell Biology and Physiology II: Cell Signaling and Metabolis
  • CAMB 6970 Biology of Stem Cells
  • CAMB 7520 Genomics
  • CBE 5170 Principles of Genome Engineering
  • CBE 5540 Engineering Biotechnology
  • CHEM 5510 Biological Chemistry
  • CIS 5350 Introduction to Bioinformatics (also offered as GCB 5350 and MTR 5350)
  • GCB 5270 Genetics for Computational Biology
  • IMUN 5060 Immune Mechanisms
  • IMUN 5080 Immune Responses
  • IMUN 6090 Vaccines and Immune Therapeutics
  • INSC 5750 Neurobiology of Learning and Memory
  • MEAM 5550 Nanoscale Systems Biology
  • MPHY 6030 Image- Based Anatomy
  • MPHY 6070 Radiation Biology
  • MSE 5180 Structure and Function of Biological Materials
  • NGG 5720 Neuroscience Core Ii
  • NGG 5730 Neuroscience Core III
  • NGG 5750 Neurobiology of Learning and Memory
  • NGG 5870 Neurobiology of Disease
  • NGG 5880 Topics in Translational Neuroscience
  • NGG 5920 Cognitive Neuroscience of Memory
  • NGG 5930 Structural Neurobiology
  • NGG 5940 Theoretical and Computational Neuroscience
  • NGG 5970 Neural Development, Regeneration and Repair
  • NGG 5980 Advanced Systems Neuroscience
  • NGG 6180 Recovery after Neural Injury
  • NGG 6310 Cognitive Neuroscience Affect
  • NGG 6320 Cognitive Neuroscience Vision
  • PHRM 5310 Intro to Genome Science
  • PHRM 5700 Principles of Cardiovascular Biology
  • PHRM 6000 Medical Pharmacology
  • PHRM 6230 Fundamentals of Pharmacology
  • PSYC 5470 Foundations of Social, Cognitive, and Affective Neuroscience
  • PSYC 5490 A Neuroscience Perspective of Artificial Intelligence
  • REG 6210/CAMB 7070/MTR 6210  Cell and Gene Therapy

2 Bioengineering graduate courses (must be BE courses) (2 CU)

BE 5020 From Biomedical Science to the Marketplace

This course explores, through own work (this is, own discovery) the transition from fundamental knowledge to its ultimate application in a clinical device or drug. Emphasis is placed upon factors that influence this transition and upon the integrative requirements across many fields necessary to achieve commercial success. Special emphasis is placed upon entrepreneurial strategies, intellectual property, and the FDA process of proving safety and efficacy. Graduate students or permission of the instructor.

Fall

1 Course Unit

BE 5040 Biological Data Science II: Data Mining Principles for Epigenomics

This course will teach upper level undergraduates and graduate students how to answer biological questions by harnessing the wealth of genomic and epigenomic data sets generated by high-throughput sequencing technologies. Graduate students or permission of the instructor

Fall

1 Course Unit

BE 5060 Introduction to Neuroengineering

This graduate-level course offers a comprehensive introduction to the interdisciplinary field of neuroengineering, focusing on the integration of neuroscience and engineering principles to advance our understanding of the nervous system and develop innovative technologies for neural interfacing and control. Through in-class lectures and focused hands-on problems, students will learn the fundamentals of neurophysiology, as well as statistical analysis of neural signals. The course will also provide the students with an overview of non-electrical neural I/O modalities, such as neurophotonics, magnetic, mechanical, and chemical methods. By the end of the course, students will gain a deeper understanding of the state-of-the art methods used in modern system neuroscience, neuromodulation systems, neuroprosthetics, and brain-computer interfaces.

Fall

1 Course Unit

BE 5100 Biomechanics and Biotransport

The course is intended as an introduction to continuum mechanics in both solid and fluid media, with special emphasis on the application to biomedical engineering. Once basic principles are established, the course will cover more advanced concepts in biosolid mechanics that include computational mechanics and bio-constitutive theory. Applications of these advanced concepts to current research problems will be emphasized.

Spring

1 Course Unit

BE 5120 Bioengineering III: Biomaterials

This course provides a comprehensive background in biomaterials. It covers surface properties, mechanical behavior and tissue response of ceramics, polymers and metals used in the body. It also builds on this knowledge to address aspects of tissue engineering, particularly the substrate component of engineering tissue and organs. General Chemistry, basic biomechanics.

Fall

1 Course Unit

BE 5130 Human Centered Design for Clinical Emergency Medicine

This capstone course is a project-based experience for graduate students where they will effectively serve as engineering design consultants for Penn Department of Emergency Medicine. Selected students should have familiarity of engineering fundamentals and will have the opportunity to use those skills to solve challenges facing two premier emergency departments. This flipped-classroom course combines lectures, significant asynchronous laboratory and clinical immersion experiences. By the end of the course, students will use human centered design and engage effectively with clinical stakeholders to develop a functional prototype and collect preliminary data on their solution that will be presented to Emergency Medicine Leadership.

Fall or Spring

1 Course Unit

BE 5140 Rehab Engineering and Design

Students will learn about problems faced by disabled persons and medical rehabilitation specialists, and how engineering design can be used to solve and ameliorate those problems. The course combines lectures, multiple design projects and exercises, and field trips to clinical rehabilitation facilities. Students will have substantial interaction with clinical faculty, as well as with patients. Prerequisite: Graduate students or permission of the instructor.

Fall

Also Offered As: IPD 5040

1 Course Unit

BE 5160 Introduction to High-Performance Scientific Computing

Research problems in the domain of physical, biological and biomedical sciences and engineering often span multiple time and length-scales from the molecular to the organ/organism, owing to the complexity of information transfer underlying biological mechanisms. Multiscale modeling (MSM) and high-performance scientific computing (HPC) have emerged as indispensable tools for tackling such complex problems. However, a paradigm shift in training is now necessary to leverage the rapid advances, and emerging paradigms in HPC — GPU, cloud, exascale supercomputing, quantum computing — that will define the 21st century. This course is a collaboration between Penn, UC Berkeley, and the Extreme Science and Engineering Discovery Environment (XSEDE) which administers several of the federally funded research purpose supercomputing centers in the US. It will be taught as a regular 1 CU course at Penn by adopting a flip-classroom/active learning format. The course is designed to teach students how to program parallel architectures to efficiently solve challenging problems in science and engineering, where very fast computers are required either to perform complex simulations or to analyze enormous datasets. The course is intended to be useful for students from many departments and with different backgrounds, e.g., scholar of Penn Institute for Computational Science, although we will assume reasonable programming skills in a conventional (non-parallel) language, as well as enough mathematical skills to understand the problems and algorithmic solutions presented.

Fall or Spring

Also Offered As: CBE 5060

1 Course Unit

BE 5180 Optical Microscopy

An introduction to the fundamental concepts of optics and microscopy. Geometrical optics: ray tracing, optical elements, imaging systems, optical aberrations. Physical optics: the electromagnetic spectrum, the wave equation, diffraction, interference and interferometers, optical resolution limits, optical coherence, lasers. Microscopy methods: phase contrast, differential interference contrast, fluorescence microscopy, confocal microscopy, multiphoton microscopy, optical coherence tomography, superresolution microscopy.

Fall

Prerequisite: MATH 2400

1 Course Unit

BE 5210 Brain-Computer Interfaces

The course is geared to advanced undergraduate and graduate students interested in understanding the basics of implantable neuro-devices, their design, practical implementation, approval, and use. Reading will cover the basics of neuro signals, recording, analysis, classification, modulation, and fundamental principles of Brain-Machine Interfaces. The course will be based upon twice weekly lectures and “hands-on” weekly assignments that teach basic signal recording, feature extraction, classification and practical implementation in clinical systems. Assignments will build incrementally toward constructing a complete, functional BMI system. Fundamental concepts in neurosignals, hardware and software will be reinforced by practical examples and in-depth study. Guest lecturers and demonstrations will supplement regular lectures. BE 3010 (Signals and Systems) or equivalent, computer programming experience, preferably MATLAB (e.g., as used the BE labs, BE 3100). Some basic neuroscience background (e.g. BIOL 2310, BE 3050, INSC core course), or independent study in neuroscience, is required. This requirement may be waived based upon practical experience on a case by case basis by the instructor.

Spring

Also Offered As: NGG 5210

1 Course Unit

BE 5260 Immunology for Bioengineers

Immunology is fast growing field that is critical to human health and therapeutic development and engineering. To better prepare bioengineers for a career in immunotherapy and biotech areas, it is essential for them to learn the fundamental knowledge of the immune system and the diseases associated as well as common and emerging technologies used in immunological research. This will not only enable the students to communicate more effectively in a multidisciplinary team, it will also empower them to take advantage of their training in engineering and mathematics to develop tools to analyze the immune system with great depth, solve important questions in immunology, and engineering new therapeutics. Therefore, the goal of this course is to provide the immunology foundation for engineering students and technical background of commonly used tools and emerging technologies in immunological research. The course is open to upper level undergraduate students who have taken courses in biochemistry and/or cell biology.

Fall

Mutually Exclusive: BE 4260

1 Course Unit

BE 5270 Immune Engineering

This course would target graduate students and upper level undergraduate students. This course introduces to students the concept of immune engineering that ranges from vaccine design to cancer immunotherapy and cutting edge tools recently developed in these areas. It is best suited for graduate students and upper level undergraduate students who have had cell biology and immunology. We will build on the topics covered in Immunology and explore deeper questions and applications in cancer immunotherapy, infection, and auto-immune diseases, and high-throughput immune profiling technologies. The course will use a combination of lectures, journal clubs, and a final project presentation that will be discussed mirroring NIH study section format. The course is open to graduate students and upper level undergraduate students who have taken courses in biochemistry and/or cell biology.

Fall or Spring

1 Course Unit

BE 5280 Applied Medical Innovation I

Applied Medical Innovation I: Bedside to Bench is a hands-on, project-based team design experience for graduate students, offered in partnership with the Center for Health, Devices, and Technology (Penn Health Tech). The course acts as an idea INCUBATOR for projects originating from unmet clinical needs, identified by clinical collaborators, industry sponsors, and Penn Health Tech partners. By the end of this course, students will understand all aspects of medical device design, innovation, and entrepreneurship, including the importance of a clear problem definition and stakeholder input, an introduction to engineering design principles, and how to navigate the complex pathway by which these products reach patients. The end point of the semester is a final pitch (outlining the need, the solution, and the business opportunity) and a functional prototype with initial proof of concept data. The course is open to all graduate and senior undergraduate students (pre-application required).

Fall

1 Course Unit

BE 5290 Applied Medical Innovation II

Applied Medical Innovation II: Bench to Bedside is a hands-on, interdisciplinary, project experience for graduate students, offered in partnership with the Center for Health, Devices, and Technology (Penn Health Tech). The course acts as device ACCELERATOR for projects originating from Applied Medical Innovation I and Penn Health Tech. Students partner with experienced technical teams (clinicians + engineers) to create a commercialization plan for real-world, cutting-edge medical technologies under development at Penn. Students work closely with their interdisciplinary team to identify and validate the clinical need, stakeholder requirements, and business case in order to de-risk the technology, increase commercial potential, and package the idea for follow-on investment. In the second half of the course, students will also gain exposure to medical technology entrepreneurship and investing. The course is open to all graduate and senior undergraduate students (pre-application required).

1 Course Unit

BE 5300 Theoretical and Computational Neuroscience

This course will develop theoretical and computational approaches to structural and functional organization in the brain. The course will cover: (i) the basic biophysics of neural responses, (ii) neural coding and decoding with an emphasis on sensory systems, (iii) approaches to the study of networks of neurons, (iv) models of adaptation, learning and memory, (v) models of decision making, and (vi) ideas that address why the brain is organized the way that it is. The course will be appropriate for advanced undergraduates and beginning graduate students. A knowledge of multi-variable calculus, linear algebra and differential equations is required (except by permission of the instructor). Prior exposure to neuroscience and/or Matlab programming will be helpful.

Spring

Also Offered As: NGG 5940NRSC 5585PHYS 5585PSYC 5390

1 Course Unit

BE 5320 Computational Biophysics

This course targets graduate students and upper level undergraduates with a background in physical chemistry. Proteins and other biomolecules perform all of the active functions that we associate with life, from muscle contraction to sensing light and sound. Like the machines we are used to operating on macroscopic scales, these molecular machines have many moving parts that are essential to their function and dysfunction. This course introduces a framework for reasoning about such dynamics and computational tools for interrogating them.

Also Offered As: BBCB 5320, BMB 5320

1 Course Unit

BE 5370 Biomedical Image Analysis

This course covers the fundamentals of advanced quantitative image analysis that apply to all of the major and emerging modalities in biological/biomaterials imaging and in vivo biomedical imaging. While traditional image processing techniques will be discussed to provide context, the emphasis will be on cutting edge aspects of all areas of image analysis (including registration, segmentation, and high-dimensional statistical analysis). Significant coverage of state-of-the-art biomedical research and clinical applications will be incorporated to reinforce the theoretical basis of the analysis methods. Prerequisite: Mathematics through multivariate calculus (MATH 2410), programming experience, as well as some familiarity with linear algebra, basic physics, and statistics.

Fall or Spring

Also Offered As: CIS 5370MPHY 6090

1 Course Unit

BE 5400 Principles of Molecular and Cellular Bioengineering

This course aims to provide theoretical and conceptual principles underlying biomolecular and biological systems. The course will start with basic and advanced concepts in physical chemistry and thermodynamics and introduce statistical mechanics as a tool to understand molecular interactions. The applications will be of relevance to bioengineering and biology disciplines. The course will not shy away from mathematical formulations and will stress the molecular perspective. This course explores physical biology of the cell across several length and timescales, while simultaneously emphasizing molecular specificity and clinical implications such as disease outcome or biomedical applications. The course emphasizes how the basic tools and insights of engineering, physics, chemistry, and mathematics can illuminate the study of molecular and cell biology to make predictive biomedical models and subject them to clinical validation. Drawing on key examples and seminal experiments from the current bioengineering literature, the course demonstrates how quantitative models can help refine our understanding of existing biological data and also be used to make useful clinical predictions. The course blends traditional models in cell biology with the quantitative approach typical in engineering, in order to introduce the student to both the possibilities and boundaries of the emerging field of physical systems biology. While teaching physical model building in cell biology through a practical, case-study approach, the course explores how quantitative modeling based on engineering principles can be used to build a more profound, intuitive understanding of cell biology. Worksheets will be integral to this course. Recitation will comprise of biweekly illustrations of problems and concepts from the worksheets and biweekly quizzes

Fall or Spring

Also Offered As: CBE 5400

1 Course Unit

BE 5470 Fundamental Techniques of Imaging

This laboratory course covers the fundamentals of modern medical imaging techniques. Students will participate in a series of hands-on exercises, covering the principals of X-ray imaging, CT imaging, photoacoustic imaging, diffusion tensor imaging, localized magnetic resonance (MR) spectroscopy, MR contrast agents, diffuse optical spectroscopy, and bioluminescence imaging. Each lab is designed to reinforce and expand upon material taught in BE 4830/BE 5830 Molecular Imaging and MMP 5070 Physics of Medical Imaging. Graduate students or permission of the instructor.

Spring

1 Course Unit

BE 5500 Continuum Tissue Mechanics

This course introduces tensor calculus and continuum mechanics, with a focus on finite-deformation behavior of biological tissues including skin, tendon/ligament, cartilage, bone, blood vessels, nerves. Senior/Graduate Student in Bioengineering or permission of the instructor.

Spring

1 Course Unit

BE 5510 Biomicrofluidics

The focus of this course is on microfluidics for biomedical applications. Topics to be covered in the first half of this course include microscale phenomena, small-scale fabrication techniques, and sensing technologies that are often leveraged in the development of microfluidic systems for the study of biomolecules, cells, tissues, and organs in living biological systems. In the second half of this course, strong emphasis will be placed on the application of microfluidics in cell biology, bioanalytical chemistry, molecular biology, tissue engineering, and drug discovery. Prereqisite: Experience with an undergraduate level fluid mechanics course is preferred. Examples of relevant SEAS courses include BE 3500 (Biotransport), CBE 3500 (Fuild Mechanics), and MEAM 3020 Fluid Mechanics).

Fall

1 Course Unit

BE 5530 Principles, Methods, and Applications of Tissue Engineering

Tissue engineering demonstrates enormous potential for improving human health. This course explores principles of tissue engineering, drawing upon diverse fields such as developmental biology, cell biology, physiology, transport phenomena, material science, and polymer chemistry. Current and developing methods of tissue engineering, as well as specific applications will be discussed in the context of these principles. A significant component of the course will involve review of current literature within this developing field. Graduate Standing or instructor’s permission.

Spring

1 Course Unit

BE 5550 Nanoscale Systems Biology

Nano-science and engineering approaches to systems in biology are of growing importance. They extend from novel methods, especially microscopies that invite innovation to mathematical and/or computational modeling which incorporates the physics and chemistry of small scale biology. Proteins and DNA, for example, are highly specialized polymers that interact, catalyze, stretch and bend, move, and/or store information. Membranes are also used extensively by cells to isolate, adhere, deform, and regulate reactions. In this course, students will become familiar with cell & molecular biology and nano-biotechnology through an emphasis on nano-methods, membranes, molecular machines, and ‘polymers’ – from the quantitative perspectives of thermodynamics, statistical physics, and mechanics. We specifically elaborate ideas of energetics, fluctuations and noise, force, kinetics, diffusion, etc. on the nano- thru micro- scale, drawing from very recent examples in the literature. Laboratory experiments will provide hands-on exposure to microscopies in a biological context (eg. fluorescence down to nano-scale, AFM), physical methods (eg. micromanipulation, tracking virus-scale particles or quantum dots), and numerical problems in applied biophysics, chemistry, and engineering. A key goal of the course is to familiarize students with the concepts and technology (plus their limitations) as being employed in current research problems in nanoscale systems biology, extending to nanobiotechnology. Prerequisite: Background in Biology, Physics, Chemistry or Engineering with coursework in Thermodynamics or permission of the instructor.

Fall

Also Offered As: CBE 5550MEAM 5550

1 Course Unit

BE 5560 Molecular Diagnostics for Precision Medicine

This course provides a broad overview of current molecular diagnostics that have been implemented in clinical settings. Students will gain knowledge in the field and they will apply the knowledge to come up with their own ideas on next generation molecular diagnostics that can resolve currently intractable clinical problems. The course also introduces key concepts and emerging concepts in the area of diagnostics. Topics covered in this course include point-of-care diagnostics, microfluidics, microscopy, liquid biopsy, digital assays, microfabrication, molecular probe design, biomarkers, biosensing, commercialization, and machine learning based data analysis. Upon completion of the course, students will have the ability to design their own diagnostic platforms.

Fall

1 Course Unit

BE 5570 Quantitative Principles of Drug Design

An application of fundamental quantitative principles to biological problems across a wide range of scales. Through an engineering lens, we examine biology on the genetic, molecular, cellular, and population level. Using this information, we can begin to rationally engineer safe and effective biologics. Emphasis is placed on quantitative modeling in MATLAB/Python and immunotherapy design. Prerequisites: Pre-reqs for UG students ENM 2400 or Math 2400, BE 3090BE 3100 or by permission of the instructor. Recommended: Introduction to Coding Course for MATLAB or Python at the level of ENGR 1050

1 Course Unit

BE 5580 Principles of Biological Fabrication

BE 558 introduces methodological approaches that are currently used for the de novo construction of biological molecules – primarily, nucleic acids and proteins – and how to use these molecules to engineer the properties of cells and intact tissue. By the end of the semester, students should (i) possess a molecular-scale understanding of key biological synthesis (ii) and assembly processes, (ii) gain an intuition for how to create novel (iii) methodologies based on these existing processes, and (iii) appreciate (iv) the drivers of technology adoption (e.g. cost, time, ease, and (v) reproducibility). Throughout the course, we will place the material in context of applications in bioengineering and human health, including: protein engineering, drug discovery, synthetic biology & optogenetics, bio-inspired materials, and bio-electronic devices. Graduate standing or permission of the instructor. Undergraduate level biology, physics and chemistry.

Fall, odd numbered years only

1 Course Unit

BE 5590 Multiscale Modeling of Chemical and Biological Systems

This course provides theoretical, conceptual, and hands-on modeling experience on three different length and time scales – (1) electronic structure (A, ps); (2) molecular mechanics (100A, ns); and (3) deterministic and stochastic approaches for microscale systems (um, sec). Students will gain hands-on experience, i.e., running codes on real applications together with the following theoretical formalisms: molecular dynamics, Monte Carlo, free energy methods, deterministic and stochastic modeling, multiscale modeling. Prerequisite: Undergraduate courses in numerical analysis and physical chemistry.

Not Offered Every Year

Also Offered As: CBE 5590SCMP 5590

1 Course Unit

BE 5610 Musculoskeletal Biology and Bioengineering

The goal of this course is to educate students in core principles and expose them to cutting-edge research in musculoskeletal biology and bioengineering through (1) lectures covering the basic engineering principles, biological fundamentals, and clinical practices involved in the function, repair, and regeneration of the musculoskeletal tissues; (2) critical review and presentation by student groups of recent and seminal publications in the field related to the basic science, translation, and clinical practice of musculoskeletal biology and bioengineering, with discussion input by faculty members with relevant expertise. This course will place an emphasis on delivering multidisciplinary knowledge of cell and molecular biology, mechanics, material science, imaging, and clinical medicine as it relates to the field of musculoskeletal bioengineering and science. Graduate student standing in Engineering and/or CAMB. Undergraduate students with permission of the instructor.

Fall, odd numbered years only

1 Course Unit

BE 5620 Drug Discovery and Development

Intro to Drug Discovery; Overview of Pharmaceutical Industry and Drug Development Costs, Timelines; High Throughput Screening (HTS): Assay Design and Sensitivity Solid Phase Synthesis and Combinatorial Chemistry; Enzyme Kinetics; Fluorescence, Linearity, Inner-filter effect, quenching; Time dynamics of a Michaelis-Menton Reaction; Competitive Inhibitor; FLINT, FRET, TRF, FP, SPA, alpha-screen; Enzyme HTS (protease); Cell based screening; Fura-2 ratio, loading signaling; Gfpcalmodulin-gfp integrated calcium response; Estrogen/ERE-Luc HTS; Problems with cell based screening (toxicity, permeability, nonspecificity); Instrumentation, Robotics/Automation; Z-factor; SAR, Positioning Scanning; Microarray HTS; IC50, % Conversion in HTS and IC50, Assay Optimization.

Fall

Also Offered As: CBE 5620

1 Course Unit

BE 5630 Advanced Topics in Musculoskeletal Biology & Bioengineering

This course is designed to build on core principles from BE5610 and will expose students to cutting-edge research in musculoskeletal engineering and science through (1) short lectures on key concepts and assays followed by (2) critical review and presentation by student groups of recent publications in the field, with discussion input by faculty members with relevant expertise. The course will prepare students for advanced doctoral studies in the field of musculoskeletal biology and bioengineering.

Spring, odd numbered years only

Prerequisite: BE 5610

1 Course Unit

BE 5650 Developmental Engineering of Tissues

This course discusses systems biology approaches to understanding tissue development, homeostasis, and organogenesis. Emphasis is placed on modern technologies, models, and approaches to understanding collective cell behaviors that sculpt tissue form and function, placing developmental principles within an engineering framework. We will consider morphogenetic, mechanobiology, and micro-engineering/sensing analyses. Senior Standing in Bioengineering or permission of the instructor. In keeping with modern graduate-level engineering classes, this course will assume some basic knowledge of coding and/or willingness to learn coding practices. The course will not attempt to serve as a comprehensive introduction to developmental biology (CAMB 5110: Principles of Development is a recommended potential companion course). However, your success in the course will not require familiarity with developmental biology.

Fall

1 Course Unit

BE 5660 Networked Neuroscience

The human brain produces complex functions using a range of system components over varying temporal and spatial scales. These components are couples together by heterogeneous interactions, forming an intricate information-processing network. In this course, we will cover the use of network science in understanding such large-scale and neuronal-level brain circuitry. Prerequisite: Graduate standing or permission of the instructor. Experience with Linear Algebra and MATLAB.

Spring

Also Offered As: ESE 5660

1 Course Unit

BE 5690 Systems Biology of Cell Signaling Behavior

This course discusses the principles of cell signaling and cell decisions. We start from a molecular description of cell signaling components. The course builds towards understanding how their interactions govern cell and tissue behavior and how these processes can breakdown in disease. We conclude with a survey of modern approaches to analyze and manipulate signaling networks to study and control biological systems. Graduate, Junior or Senior standing in Bioengineering or permission of the instructor.

Spring

1 Course Unit

BE 5700 Biomechatronics

Mechatronics is the combination of mechanical, electrical and computer engineering principles in the design of electromechanical systems. Biomechatronics is the application of these principles to human biology and includes orthopaedic, hearing, respiratory, vision and cardiovascular applications. In this hands-on, project-based course, these biomechatronic systems will be explored. Students will learn the basic mechanical and electrical elements needed to complete a biomechatronic design challenge including basic circuits, design considerations, material fabrication, microcontrollers and mechanisms (e.g. converting rotational motion into linear motion). Students will carry out a final design project utilizing these building blocks. A first course in programming (Matlab and/or C++ preferred) , Senior standing in BE or permission of the instructor

Fall

1 Course Unit

BE 5710 The Goals of Scientific Inquiry

A key skill needed for a successful career in engineering and applied science is the ability to capitalize on current advances in technology (e.g., big data, data science, machine learning) to solve important problems. To gain this ability a student must go beyond an understanding of the technology itself, and instead must achieve the more challenging capacity to identify tractable problems, to formulate good questions, to initiate big ideas, to guide the advancement of science. In this course, we provide a broad and rich perspective on science as a field, laying the critical groundwork for just such achievements. Prerequisites: The course is open to all graduate students. Undergraduates must have passed Math 2410, ENM 3750 or equivalent, CIS 1200 or higher, and PHYS 0141PHIL 1800 or similar is beneficial but not required.

Spring, even numbered years only

1 Course Unit

BE 5740 Special Topics in Bioengineering

This special topics course will focus on emerging topics in Bioengineering at the macroscale from organ to population level covering genomics, epigenetics, molecular and cellular systems with focus on immunology, cancer, neuroengineering, biomechanics, and other facets of bioengineering. This course is intended for PhD students in their first year of study.

Spring

1 Course Unit

BE 5760 The Cell as a Machine

The course is a general survey of cell mechanics, emphasizing problem-based and hypothesis-testing approaches. It is based on the concept that the cell is a complex machine, and that the cell can therefore be understood by first understanding principles of complex functions in robust machines, and then understanding the design and operation of complex functions specifically in cells. The course has been offered internationally for many years using a reverse-classroom format. Lectures, which are given primarily by Michael Sheetz, former director of the Mechanobiology Institute at the National University of Singapore, are pre-recorded and viewed independently by students, who also do outside reading and prepare questions in advance of a live, remote, 2 hour question/discussion session with Dr. Sheetz. The Penn course directors are present at all question/discussion sections, and lead tutorials on site. Homework and exams are graded, and Penn course directors will review them for consistency. Other sites that will be involved in the course in the coming year include Columbia, MIT, and Berkeley. Graduate Standing or permission of the instructor.

Fall

1 Course Unit

BE 5780 Principles of Controlled Release Systems

This course provides a basic understanding of the engineering of controlled release systems specifically geared towards the development of formulations for drug delivery, which stands as a 114 billion dollar industry. The course focuses on topics at the interface between engineering and medicine, such as biomaterials, pharmacokinetics, polymer chemistry, reaction kinetics, and transport phenomena. Design of controlled release systems for transdermal, aerosol, oral, gene, and targeted cellular delivery are discussed with emphasis placed on fabrication, US FDA regulatory considerations, and the relevant physiological milieu. The course comprises (1) foundational lectures that provide the basic tools for the student to elaborate a controlled delivery system, (2) an overview of key current research on biomedical controlled release systems for different pathologies and body compartments, (3) an elevator pitch competition for original ideas that use controlled release systems, and (4) a project; plan and presentation to implement the pitched controlled release; system idea to practice design and problem-solving skills and practice basic elements of business proposal. Graduate students and senior standing in Bioengineering, Chemical and Biomolecular Engineering, or permission of the instructor.

Fall

1 Course Unit

BE 5830 Physics of Medical / Molecular Imaging

Physical principles of diagnostic radiology, fluoroscopy, computed tomography; principles of ultrasound and magnetic resonance imaging; radioisotope production, gamma cameras, SPECT systems, PET systems; diagnostic and nuclear medicine facilities and regulations. The course includes a component emphasizing the emerging field of molecular imaging.

Fall

Mutually Exclusive: BE 4830

1 Course Unit

BE 5840 The Mathematics of Medical Imaging and Measurement

The last several decades have seen major revolutions in both medical and non-medical and imaging technologies. Underlying all of these advances are sophisticated mathematical tools to model the measurement process and reconstruct images. This course begins with an introduction of the mathematical models and then proceeds to discuss the integral transforms that underlie these models: the Fourier transform, the Radon transform and the Laplace transform. We discuss how each of these transforms is inverted, both in theory and in practice. Along the way we study interpolation, sampling, approximation theory, filtering and noise analysis. This course assumes a thorough knowledge of linear algebra and a knowledge of analysis at the undergraduate level (MATH 3140 and MATH 3600 and MATH 3610, or MATH 5080 and MATH 5090).

Not Offered Every Year

Also Offered As: AMCS 5840MATH 5840

Prerequisite: MATH 1410 AND (MATH 3600 OR MATH 5080) AND (MATH 3610 OR MATH 5090)

1 Course Unit

BE 5850 Materials for Bioelectronics

Bioelectronics is an emerging field that involves the use of engineering principles to create devices for applications in biology, medicine, and health sciences. One of the most important aspects of bioelectronics is the development of communication interfaces between biological materials (cells, tissues and organs) and manmade devices for optimal energy delivery and signal transduction efficacies. Progress in materials science and engineering is bringing revolutionary advances to the biointerface design and has unlocked unprecedented applications in various biomedical fields. This course focuses on the materials science and engineering concepts that are of relevance to bioelectronics. It also introduces basic biochemical, biophysical and physiological principles that are required to understand the design and application of bioelectronic devices.

Spring

Also Offered As: MSE 5850

1 Course Unit

BE 5990 Master’s Independent Study

The purpose of BE 5990 is to allow a student to create a customized curriculum to study material beyond or outside the scope of our standard BE course offerings. Independent study is NOT a research or design project, it is a one-on-one or small-group course with a professor. The course should require an effort comparable to that of a regular course, about 10-12 hours per week. A paper or presentation is required.

Fall or Spring

1-4 Course Units

BE 6080 Medical Entrepreneurship: Commercializing Translational Science

This course provides in depth insight into the process by which health technology platforms including scientific discoveries are transformed into viable commercial entities. This includes methods to evaluate market opportunities and derisk critical assumptions within the rapidly changing academic and healthcare environment. Topics include intellectual property creation and licensing, technology transfer, regulatory pathways, raising capital/NIH SBIR/STTR grant funding, go to market strategy, market sizing, formation equity, and recruiting co-founders. The major project will involve the formation of teams that will create a defendable business plan and consummate in a presentation (pitch deck) intended to raise capital. The course will be especially valuable for students who may be considering entrepreneurial career paths including starting a company, working for an early stage venture, healthcare consulting, or assuming innovation leadership roles.

Spring

Also Offered As: MTR 6200

1 Course Unit

BE 6100 Special Topics in Neuroengineering – Interdisciplinary Intelligence Initiative Colloquium

The Intelligence Colloquium is an interdisciplinary course designed to encourage a unified understanding of intelligence. There are three levels on which we can think about intelligence: computational goals, algorithms, and implementations. Each of these levels extend through  domains of scientific enquiry such as physics, engineering, neuroscience, psychology, and economics. While many courses locally deal with relevant issues, this colloquium will aim to bring people together across disciplinary boundaries. For example, when building brain machine interfaces, engineers seek to decode the algorithm of intelligence. When constructing new substrates for computation, physicists produce new primitives for implementing intelligence. When asking about the goals of the computation psychology probes individual goals while economics often probes those of larger groups. Focusing on the core algorithms of intelligence, all these groups are now using neural networks as a way of building systems that serve as demonstration. The goal of this course is to bring people together from all these communities to train people to think cleanly and be productive in this emerging interdisciplinary space. The course aims to foster a deep learning-centric interpretation of these fields and to promote a mutual exchange of ideas and approaches. The primary mode of learning will be reading, analyzing, and presenting relevant research papers and forming well-informed opinions.

Fall or Spring

1 Course Unit

BE 6400 Mechanobiology of the Cell and its Microenvironment

This course is geared towards first and second-year graduate students in BGS/CAMB and SEAS/BE with an interest in the interface of extracellular matrix (ECM) cell biology and biomechanics. Students will learn about the ECM and adhesion receptors and their impact on the cytoskeleton and signaling, as well as fundamental concepts in biomechanics and engineered materials. We will discuss how these topics can inform the study of cell biology, physiology, and disease. An additional objective of the course is to give students experience in leading critical discussions and writing manuscript reviews. Invited outside speakers will complement the strengths of the Penn faculty. Offered in the spring semester of even years only.

Spring, even numbered years only

Also Offered As: CAMB 7030

Prerequisite: BIOM 6000

1 Course Unit

BE 6500 Advanced Biomedical Imaging Applications

The course will cover a broad range of biomedical imaging technologies including X-ray, MRI, US, molecular and optical imaging. The curriculum will focus on the design of biomedical imaging based research studies spanning from basic technology development through clinical trials. This discussion oriented course is expected prepare students for integrating imaging technology and biomedical concepts to answer biological and medical questions.

Fall

1 Course Unit

BE 6620 Advanced Molecular Thermodynamics

This course begins with a brief review of classical thermodynamics, including the development of Maxwell relationships and stability analysis. The remainder of the course develops the fundamental framework of statistical mechanics, then reviews various related topics including ideal and interacting gases, Einstein and Debye models of crystals, lattice models of liquids, and the basis of distribution function theory.

Fall

Also Offered As: CBE 6180MEAM 6620

1 Course Unit

BE 7110 Integrative plant and animal mechanobiology

This course aims to provide students with an understanding of biomechanics that spans the plant and animal kingdoms, with the goal of emphasizing principles common to both. Major concepts include 1) Plant and Animal Cell Biology; 2) Solid, Fluid, and Transport Mechanics; and 3) Integrating Biology and Mechanics – Big Questions. In addition to lectures, there will be two journal article discussion sections. Most lectures will be given by Penn faculty, although selected topics (particularly in plant biology and mechanics) will be covered by faculty at other sites through lectures broadcast remotely. The Penn director will be present at all sessions of the class. Undergraduates require special permission from the director.

Fall

Also Offered As: CAMB 7110

1 Course Unit

BE 9990 Master’s Thesis Research

For students working on an advanced research program leading to the completion of master’s thesis.

Fall, Spring, Summer

1 Course Unit

3 SEAS and or Biological Science Electives

1 general elective course

Thesis Option Requirements

If you choose to write a thesis, you will enroll in 2 units of thesis research, course number BE 9990 (formerly BE 5970)

Be sure to read the Master’s Thesis Guidelines. In choosing the thesis option, your thesis advisor may provide additional guidance on course selection and will supervise your thesis research. Thesis mentors must be selected from the Bioengineering Graduate Group.

Non-Thesis Option Requirements

If you choose not to write a thesis, you will enroll in an additional 2 units of science and engineering electives of your choice (2 CU’s).

Independent Study

Independent Study is designed to provide the student with a unique learning experience not achievable by ordinary course work. You must identify a member of the University’s Standing Faculty (it’s not necessary to choose faculty who are members in the BE Graduate Group) who is willing to direct your independent study and take responsibility for issuing your final grade.

Students must submit an application for Independent Study which will be reviewed by the graduate directors for approval. Please access the application for  independent study (BE 5990) and complete the necessary information.