to Bioengineering BE 2000 Course 4.00
- Subject
- BE
- Credits (min)
- 0.5
- Credits (max)
- 0.5
- Type
- course
- Edition
- 2026-2027
- Source
- catalog.upenn.edu
81 courses with the subject BE, each shown exactly as we captured it from the college's catalog, with every element we hold. Where the wording looks broken, that is our reading of the catalog, not the college's text.
to Bioengineering BE 2000 Course 4.00
This course investigates the application of statics and strength of materials to soft and hard biologic tissues. The course will cover simple force analyses of the musculoskeletal system and introduces the fundamentals of the mechanics of materials including axial loading, torsion and bending and their application to biomechanics. The lecture and recitation will be complemented with hands-on examples emphasizing connections between theoretical principles and practical applications.
This course investigates the application of materials science and engineering to biomedical applications, with a focus on polymers, ceramics, and metals. The course will cover concepts related to basic material fabrication and synthesis, structure and property characterization, as well as applications of biomaterials. The lecture and recitation will be complemented with laboratory examples of material assessment and characterization.
This course will cover a variety of bioengineering laboratory principles and techniques including data collection, analysis and reporting. Students will explore tools related to mechanics, materials and s electronics with applications in the bioengineering field. Corequisite with BE 2200.
/ BE 3060 Cellular Engineering 1
The biological cell is a complex machine and its function is at the root of all physiology and many pathologies. Recent advances in molecular and cell biology enable the redesign of cell function. This course aims to develop a quantitative understanding of cell function, and how we might go about changing cell function through intelligent redesign. The course covers topics ranging from receptor binding and endocytosis, cell adhesion and motility, cell function in the immune system, systems and synthetic biology, genetic knockdown and manipulation using CRISPR and gene therapy, and strategies for immunotherapy including chimeric antigen receptor therapy (carT).
BE 3090 is a one course-unit laboratory course with a focus on combining experimental and mathematical approaches to understand biological systems and solve bioengineering problems. The course content integrates concepts from mathematics, physics, signal analysis, control engineering , mass transport, and heat transfer with applications in physiology and pharmacology. Areas of emphasis are model development and validation, statistical analysis, experimental design, error analysis and uncertainty, and scientific writing.
BE 3100 is a one course-unit laboratory course on the design of technology to measure and control biological systems. The course is divided into four modules: (i) microfluidics for point of care diagnostics, (ii) synthetic biology for predicting cellular behavior, (iii) electronics and signal analysis of bioelectrical signals, and (iv) bioanalytical spectroscopy for low-cost diagnostics. Each module will have two components: (i) a series of structured learning exercises to teach key concepts and methods of the topic that we are studying, and (ii) a design challenge, in which the understanding gained in the first component is used to design a solution to an open ended bioengineering challenge.
Soft matter is found in diverse applications including sports (helmets & cloths); food (chocolate, egg); consumer products (e.g., lotions and shampoo); and devices (displays, electronics). Whereas solids and liquids are typically hard and crystalline or soft and fluid, respectively, soft matter can exhibit both solid and liquid like behavior. In this class, we investigate the thermodynamic and dynamic principles common to soft matter as well as soft (weak) forces, self-assembly and phase behavior. Classes of matter include colloidal particles, polymers, liquid crystalline molecules, amphiphilic molecules, biomacromolecules/membranes, and food.FallAlso Offered As: MSE 3300Prerequisite: CHEM 1021 OR MSE 2200 OR BE 22001 Course Unit
Introduction to basic principles of fluid mechanics and of energy and mass transport with emphasis on applications to living systems and biomedical devices.
Introduction to the integration of biomedical engineering in clinical medicine through lectures and a preceptorship with clinical faculty. This course is for BE majors ONLY, with preference given to BSE students.
cannot count both BIOL 4004 and BE 4260/ BE 5260 towards concentration) or BE 5260 Immunology for Bioengineers or BIOL 4004Immunobiology
Lab-based course where students learn the fundamentals of medical device design through hands-on projects using microcontrollers. Students first learn basic design building blocks regularly employed in microcontroller-based medical devices, and then carry out a small design project using those building blocks. Projects are informed by reverse-engineering of competing products, FDA regulations, and marketplace considerations. Prerequisite: Junior or Senior BE Majors only. Students who have taken ESE 3500 or a similar course may not enroll. Permission of instructor required if course prerequisites not met.Spring1 Course Unit
Students will learn the process of developing medical devices that fulfill unmet patient needs. Students will be equipped with an understanding of what is required to lead a startup venture in medical devices including regulatory, legal, fundraising, team building and leadership. In lab, students will develop a proof-of-concept prototype device. Students will pitch their ideas to real med tech investors . The successful student will leave the class with the knowledge, skills and confidence to lead a startup venture in medical devices. If desired by the student, the proof-of-concept device can be used as the basis for their senior design project. Junior standing in Bioengineering or permission of the instructor if course prerequisite is not met.Spring1 Course Unit
Introduction to the mathematical, physical and engineering design principles underlying modern medical imaging systems including x-ray computed tomography, ultrasonic imaging, and magnetic resonance imaging. Mathematical tools including Fourier analysis and the sampling theorem. The Radon transform and related transforms. Filtered backprojection and other reconstruction algorithms. Bloch equations, free induction decay, spin echoes and gradient echoes. Applications include one-dimensional Fourier magnetic resonance imaging, three-dimensional magnetic resonance imaging and slice excitation.
This course will provide a comprehensive survey of modern medical imaging modalities and the emerging field of molecular imaging. The basic principles of X-ray, ultrasound, nuclear imaging, and magnetic resonance imaging will be reviewed. The course will also cover concepts related to contrast media and targeted molecular imaging. Topics to be covered include the chemistry and mechanisms of various contrast agents, approaches to identifying molecular markers of disease, ligand screening strategies, and the basic principles of toxicology and pharmacology relevant to imaging agents.
An intensive independent study experience on an engineering or biological science problem related to bioengineering. Requires preparation of a proposal, literature evaluation, and preparation of a paper and presentation. Regular progress reports and meetings with faculty advisor are required. Sophomore, Junior and Senior BE majors only.Fall or Spring1 Course Unit
Second semester of an independent project. Sophomore, Junior and Senior BE majors only.
Group design projects in various areas of bioengineering. Project ideas are proposed by the students in the Spring semester of the Junior year and refined during the Fall semester. The course guides the students through choosing and understanding an impactful biomedical problem, defining characteristics of a successful design solution to eliminate or mitigate a problem or fulfill a need, identifying and prioritizing constraints, creatively developing potential design solutions, iteratively refining design options, defining and implementing an optimal solution , and evaluating how well the solution fulfills the need. Final oral and written reports are required. Also emphasized are teamwork, project management, time management, regulations/standards, and effective communication. Seniors in BE or Department Permission.
BE Elective (4000 or 5000 level) 2 SEAS Engineering (EUNG) (https://catalog.upenn.edu/ 2 attributes/eung/) Math and Natural Science
Biological 1 Thesis in Data Biomedical Science I - Science Fundamentals Professional Elective 1 of 1 SS, H, or TBS 1
BE Elective (4000 or 5000 level)
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.
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.
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.
and Infrastructure Machine learning, analysis, and meaningful visualizations can provide significant insights into clinical research datasets. One of the challenges is to make these tools, and workflows available at scale in a meaningful way for clinicians, data scientists, and patients. In this course, we will focus on cloud-based mechanisms and infrastructure to make analysis workflows broadly available to a wide range of potential users. Students will implement an analytic workflow related to a clinical research dataset and ultimately deploy the workflow as a publicly available service on the internet using AWS services. We will discuss all components related to the development life-cycle of cloud based analytic services including testing, logging, deploying infrastructure, APIs, front-end development and the value of doing research in the cloud. It is expected that students are comfortable with Python coding and have taken a data science class prior to enrolling in this course. Pre-requisites: - Students should have significant experience with programming in Python. - BMIN 5030 or BMIN 5200 or equivalent. - Students are interested in learning to work within the AWS environment. Also Offered As: BMIN 5100 1 Course Unit
Course BE 5400 Principles of Molecular and Cellular Units Bioengineering 2 BE 5530 Principles, Methods, and Applications of
This capstone course is a project-based experience for graduate students where they will effectively serve as design consultants for Penn Department of Emergency Medicine. Selected students should have familiarity of technical fundamentals, such as engineering design and data analysis, and will have the opportunity to use those skills to solve challenges facing two premier emergency departments. This flipped- classroom course combines lectures and significant asynchronous laboratory and clinical immersion experiences. By the end of the course, students will use human centered design to develop a functional prototype and collect preliminary data on their solution, which will be presented to Emergency Medicine Leadership.
2 BE 5180 Optical Microscopy
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.
Course BE 5370 Biomedical Image Analysis Units BE 5470 Fundamental Techniques of Imaging 2 BE 5810 Techniques of Magnetic Resonance
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.SpringAlso Offered As: NGG 52101 Course Unit
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.
BE/CBE 5550 Nanoscale Systems Biology
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).Fall1 Course Unit
BE/CBE 5620 Drug Discovery and Development
1 Neuroscience
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
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.
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 or 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
Our theoretical and computational capabilities have reached a point where we can do predictions of materials on the computer. This course will introduce students to fundamenta l concepts and techniques of atomic scale computational modeling. The material will cover electronic structure theory and chemical kinetics. Several well-chosen applications in energy and chemical transformations including study and prediction of properties of chemical systems (heterogeneous, molecular, and biological catalysts) and physical properties of materials will be considered. This course will have modules that will include hands-on computer lab experience and teach the student how to perform electronic structure calculations of energetics which form the basis for the development of a kinetic model for a particular problem, which will be part of a project at the end of the course. Thermodynamics, Kinetics, Physical Chemistry, Quantum Mechanics. Undergraduates should consult and be given permission by the instructor.
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.
Course BE 5700 Biomechatronics
2 BE 5560 Molecular Diagnostics for Precision
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.
or CBE 5550 Nanoscale Systems Biology or MEAM 5550
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.
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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 only1 Course Unit
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 5590, SCMP 5590 1 Course Unit
2 Bioengineering Total Course Units 4 Therapeutics, Drug Delivery & Nanomedicine Code Title Course
or CBE 5620 Drug Discovery and Development
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 1 Course Unit
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.
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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 0141. PHIL 1800 or similar is beneficial but not required. Spring, even numbered years only 1 Course Unit
Responsible Conduct of Research Requirement
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.
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.
This course provides fundamental understanding of controlled release system engineering with emphasis on biomaterial design and drug delivery formulation development. Students explore interdisciplinary topics at the engineering-medicine interface, including biomaterials science, pharmacokinetics, polymer chemistry, reaction kinetics, and transport phenomena. The curriculum covers controlled release system design across multiple delivery routes - transdermal, pulmonary, oral, gene therapy, and targeted cellular delivery - with particular attention to fabrication methods, FDA regulatory pathways, and physiological constraints. The course integrates four complementary components: (i) foundational lectures establishing core principles for controlled delivery , system design; (ii) literature-based discussions featuring invited field experts presenting current research; (iii) comparative platform analysis through debate-style group presentations examining different delivery technologies for specific therapeutic challenges; and (iv) analytical reports with strategic recommendations, allowing students to practice design methodology and scientific proposal development. Prerequisites: Graduate standing or senior-level undergraduate in Bioengineering, Chemical and Biomolecular Engineering, or instructor permission.
Detailed introduction to the physics and engineering of magnetic resonance imaging as applied to medical diagnosis. Covered are magnetism spatial encoding principles, Fourier analysis, spin relaxation, imaging pulse sequences and pulse design, contrast mechanisms, chemical shift, flow encoding, diffusion and perfusion, and a discussion of the most relevant clinical applications. Also Offered As: BMB 5810 1 Course Unit
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.
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 5840, MATH 5840 (MATH 3610 OR MATH 5090) 1 Course Unit
or MSE 5850Materials for Bioelectronics
An introduction to systems neuroscience and neuroengineering applications to systems neuroscience and computational neuroscience. The focus will be on the "virtuous cycle" between advanced neuroengineering to develop technology to measure and manipulate brain function; this increases our understanding of brain function, which in turn, leads to improved devices, and eventual application to clinical problems. The course spans human and non-human primate research. The core brain systems for sensory, motor, cognitive, emotional functions will be introduced and their relevance for neuroengineering discussed. 1 Course Unit University of Pennsylvania Catalog 1201
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Traditional neuroscience courses present a fragmented view of the field, cataloging empirical observations and theoretical constructs without providing strong conceptual links between them. The discipline has yet to establish core principles that promise an overarching understanding. This course, heavily leaning on deep learning, will provide such an overarching way of thinking about brains. The classes will mostly be lecture based, building on an upcoming textbook. Homework will primarily be the coding up and analyzing of models.
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 1 Course Unit 2026-27 Catalog | Generated 08/03/26
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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.
Biomedical Science Course (Attribute EBPS) 1 Statistics and Domain Math Course (Attribute EBPM) 1 nt BE 9999 Independent Study Research 1
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.
This course provides training in the practical aspects of teaching. The students will work with a faculty member to learn and develop teaching and communication skills. As part of the course, students will participate in a range of activities that may include: giving lectures, leading recitations, supervising laboratory experiments, developing instructional laboratories, developing instructional material, preparing and grading homework assignments and solution sets, and preparing examinations. Feedback on the recitations will be provided to the student by the faculty responsible for the course. The course is graded on a Satisfactory/Unsatisfactory basis. The evaluation will be based on comments of the students taking the course and the impressions of the faculty. 1 Course Unit 2026-27 Catalog | Generated 08/03/26
Total Course Units 19 Selected in consultation with research advisor. Course Attribute lists for EPBS (https://catalog.upenn.edu/attributes/epbs/), EPBM (https://catalog.upenn.edu/attributes/epbm/), and EPBF (https://
Be sure to read the Master's Thesis Guidelines (https:// be.seas.upenn.edu/masters/degree-requirements/). In choosing the thesis option, your thesis advisor may provide additional guidance on course selection and will supervise your thesis research. The director of the Bioengineering MSE program will help you find a mentor, traditionally selected from the Bioengineering Graduate Group. (http:// www.be.seas.upenn.edu/about-research/grad-group.php)
for up to two credits of didactic classes (BE Fundamentals, Biological Science, or Statistics and Domain Math). Doctoral students are expected to maintain full-time status and to enroll in BE 9999 Independent Study Research while conducting research, in year one and two in consultation with their advisor. A student should enroll in BE 9950 in year three and beyond once they 2026-27 Catalog | Generated 08/03/26 advance to candidacy. A student must be enrolled in BE 9950 in their final semester.
Source: University of Pennsylvania's catalog, linked per course · table learning_unit · CourseShelf publish 59