PhD Program Mission Statement
Biomedical Engineering (BME) has emerged as one of the most exciting interdisciplinary research fields in modern science. Biomedical engineers apply modern approaches from the experimental life sciences in conjunction with theoretical and computational methods from the disciplines of engineering, mathematics and computer science to the solution of biomedical problems of fundamental importance. The Biomedical Engineering Graduate Program of the Johns Hopkins University is designed to train engineers to work at the cutting edge of this exciting discipline.
The cornerstone of the program is our belief in the importance of
in-depth training of students in both life sciences and modern engineering,
mathematics and computer science and in the conduct of original research
leading to the doctoral dissertation. In-depth training in life sciences
is achieved in one of two ways. First, incoming PhD students may
enroll in the first year basic sciences curriculum of the Johns Hopkins
University School of Medicine. This is a unique and intensive curriculum
covering a broad range of topics including molecules and cells, human
anatomy, immunology, physiology and neuroscience. Students choosing
this option typically devote their entire first academic year to
these courses. This curriculum is an excellent way to build a broad
and solid foundation in the life sciences. Second, students may elect
alternative life sciences curricula. These curricula have been carefully
designed to provide training in areas of the life sciences that are
appropriate to each of the program’s research areas. This option is of particular value to students who enter the program having a strong background in the life sciences. In-depth training in engineering, mathematics and computer science is achieved through elective courses, with choice of electives reflecting the research interests of each student. Detailed curricula have been developed in each of the program’s
research areas to assist students in making these choices.
The following sections describe program administration, research areas, general requirements and specific research and training curricula.
Progam Administration
Reza Shadmehr, Ph.D.
- Ph.D. Program Co-Director
shadmehr@jhu.edu
Office Phone: (410) 614-2458, FAX:
(410) 502-2826
720 Rutland Ave., 410 Traylor
Building
Baltimore MD 21205
David T. Yue, M.D., Ph.D.
- Ph.D. Program Co-Director
dyue@jhmi.edu
Office Phone: (410) 955-0078, FAX:
(410) 614-8269
720 Rutland Ave., 713 Ross
Building
Baltimore MD 21205
Hong Lan - Administrative Director, BME Ph.D. Program
hlan1@jhmi.edu
Office Phone: (410) 614-4280
Traylor 406
720 Rutland Ave.
Baltimore MD 21205
Research and Training Areas
Research in the Department focuses on seven general areas:
Cell and Tissue Engineering
Tissue engineering, one of the most exciting and rapidly growing areas in biomedical engineering, offers vast potential for changing traditional approaches to meeting many critical health care needs. In the years to come, many tissues or organs may be strong candidates for engineering reconstruction, including bone, cartilage, liver, pancreas, skin, blood vessel and peripheral nerve.
More about Cell and Tissue Engineering
Cardiovascular Systems
As the country's number one killer, cardiovascular disease poses a major health problem for thousands of individuals. In response to this national concern, the Whitaker Biomedical Institute is bringing together researchers from across the disciplines of physiology, biophysics, biomechanics, mathematics, systems identification and computer modeling to work collaboratively on a number of cardiovascular research projects.
More about Cardiovascular Systems
Medical Imaging
Technological advances now allow us to image the human body at scales from a single molecule to the whole body. Researchers are linking the anatomical data, collected with emerging imaging technologies, to computer simulations to form truly functional images of individual patients. These images will allow physicians not only to see what a patient's organs look like but also how they are functioning even at the smallest dimensions. A major challenge is how to store, analyze, distribute, understand and use the enormous amount of data associated with every one of these thousands of images.
More about Medical Imaging
Systems Neuroscience
The brain is perhaps the greatest and most complicated learning system that exercises its control over virtually every aspect of our behavior. The systems neuroscience area is dedicated to understanding its architecture and how it learns and controls a variety of functions. Dramatic advances in experimental methods for studying neural systems have occurred during the past decade. Investigators in this area share a common desire to produce quantitative models of information coding and processing in neural systems.
More about Systems Neuroscience
Molecular and Cell Systems
Each of the human body’s approximately 100 trillion cells can perform most of the fundamental functions of life. Under- standing how molecules interact to produce these functions is a central biological problem. Conquering this staggering challenge holds the key to designing effective treatments for disease.
More about Molecular and Cell Systems
Bioinformatics and Computational Biology
Biomedical research is being revolutionized by new technologies for generating high throughput data. Research in bioinformatics in biomedical engineering and computational medicine is currently focused on representing and analyzing such data.
More about Bioinformatics and Computational Biology
Computational Modeling
Vast amounts of genetic and biochemical information are becoming rapidly available. Every day, Hopkins biomedical engineering researchers draw on this data as they combine the knowledge of the human genome with the massive power of modern computers to construct simulations of human organs. These simulations or models will be so realistic that they can be used to design and test novel therapeutics, including medical devices, pharmaceuticals and clinical procedures.
More about Computational Modeling
Questions?
Last Updated: 12/20/2012 | Legal Notice
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