Translational Bioengineering (PhD)
Applicants must meet Graduate School admission requirements along with additional program requirements. Applicants must, as a minimum, have completed a Bachelor’s Degree in Engineering from an accredited program or a similar field with a 3.25 cumulative GPA to be considered for admission. Applicants with an undergraduate GPA of 3.0 will be considered for provisional acceptance. The ideal applicant will have completed or be in the process of completing either a Master’s (MS or MEng) Degree in Engineering at the time of application.
Applicants must submit:
a. A completed graduate application for the Graduate School
b. An application fee
c. Official transcript(s) from each college attended certifying at least a bachelor's degree. All transcripts not in English must be certified as authentic and translated verbatim into English.
d. Personal statement (include intended area of study and/or research interest, previous experience related to bioengineering and how the PhD in Translational Bioengineering will allow them to fulfill their career goals as identified by their focus are of interest).
e. Resume/CV
f. Three letters of recommendation
g. Students whose native language is non-English or degree is from a non-US accredited institution are required to submit TOEFL scores (administered by the Educational Testing Service). A minimum TOEFL score of 79 or high on the internet-based test is required. Alternatively, a minimum of 6.5 on the Internation English Language Testing System will be accepted or Duolingo score of 105
h. Optional Graduate Record Exam (GRE)
Program Requirements
To earn the Doctor of Philosophy in Translational Bioengineering, students are required to successfully complete the following:
- 47 credit hours of course work beyond their bachelor's degree (18 core credit hours, 9 specialty are credit hours, and 20 guided elective credit hours)
- Participate in the Bioengineering Seminar Series (75% attendance rate and one presentation/year as a Doctoral candidate)
- Pass the preliminary examination
- Pass the Dissertation proposal
- Successfully defend a dissertation
- Submit three or more peer-reviewed journal papers representing their original dissertation research
| Code | Title | Hours |
|---|---|---|
| Required Core Courses | ||
| BE 601 | Bioengineering Seminar | 1 |
| BE 601 | Bioengineering Seminar | 1 |
| BE 601 | Bioengineering Seminar | 1 |
| BE 603 | Bioengineering Research Ethics | 2 |
| BE 621 | Bioinstrumentation | 4 |
| BE 654 | Advanced Physiology for Engineers | 3 |
| BE 695 | Bioengineering Research Design & Methods | 3 |
| ME 565 | Advanced Engineering Mathematics I | 3 |
| Minimum Total Hours | 18 | |
Students must choose 9 credit hours from one of the following focus areas:
- Molecular & Tissue Engineering (MTE)
- Bioimaging & Biocomputational Modeling (BBM)
- Bioelectrical & Biomedical Devicies (BBD)
- Biomechanics & Rehabilitation (BR)
| Code | Title | Hours |
|---|---|---|
| Focus Area: Molecular & Tissue Engineering (MTE) | ||
| Choose 9 hours from the courses below: | 9 | |
| Nanoscale Bioengineering: Application and Methodology of Nanobiomaterials in Bioengineering | ||
| Introduction to Tissue Engineering | ||
| Tissue and Molecular Biology Techniques Laboratory | ||
| Advanced Biomaterials | ||
| Cellular Mechanobiology in Cancer | ||
| Techniques in Biomolecular Interactions | ||
| Molecular Biology | ||
| Minimum Total Hours | 9 | |
| Code | Title | Hours |
|---|---|---|
| Focus Area: Bioimaging and Biocomputational Modeling (BBM) | ||
| Choose 9 hours from the courses below: | 9 | |
| Medical Image Computing | ||
| Machine Learning in Medicine | ||
| Introduction to Artificial Intelligence in Bioengineering | ||
| Modeling of Biological Phenomena | ||
| Machine Learning in Python | ||
| Computer Tools for Medical Image Analysis | ||
| Artificial Intelligence Techniques in Digital Pathology | ||
| Computational Methods for Medical Image Analysis | ||
| Artificial Intelligence and Radiomics | ||
| Simulation and Modeling of Discrete Systems | ||
| Digital Image Processing | ||
| Minimum Total Hours | 9 | |
| Code | Title | Hours |
|---|---|---|
| Focus Area: Bioelectrical & Biomedical Devices (BBD) | ||
| Choose 9 hours from the courses below: | 9 | |
| LabVIEW for Bioengineers | ||
| Advanced Computer-Aided Design and Manufacturing for Bioengineers | ||
| Biomedical Acoustics | ||
| Artificial Organs | ||
| Fundamentals of Microfabrication and MEMS | ||
| Cardiovascular Dynamics | ||
| Advanced Biomaterials | ||
| Minimum Total Hours | 9 | |
| Code | Title | Hours |
|---|---|---|
| Focus Area: Biomechanics & Rehabilitation (BR) | ||
| Choose 9 hours from the courses below: | 9 | |
| Optimum Design Methods | ||
| Biomechanical Computer Modeling and Simulation of Human Movement | ||
| Cardiovascular Dynamics | ||
| Injury Biomechanics | ||
| Rehabilitation Engineering and Assistive Technology | ||
| Kinematics and Kinetics of Human Movement | ||
| Biofluid Mechanics | ||
| Minimum Total Hours | 9 | |
Specialization Area Guided Electives
Courses in Specialization Area must be unique from those taken to fulfill the Focus Area requirement, and must follow a track listed below. Students must work with their advisor to establish a Plan of Study for Specialization Courses. All Specialization courses must be approved by the student's advisor prior to registration.
Traditional Bioengineering (T)
18 credit hours from those listed below with a minimum of six (6) credit hours in engineering courses and Teaching Practicum, BE 668 (two (2) credit hours).
Clinical Translational Bioengineering (C)
12 credit hours from list below designated as ASNB, BIOC, MBIO, OBIO, or PHZB; remaining six (6) credit hours in engineering courses and Clinical Practicum, BE 692 (two (2) credit hours).
Entrepreneurship of Bioengineering Technologies (E)
12 credit hours from list below designated as ENTR; remaining six (6) credit hours in engineering courses and Teaching Practicum, BE 668 (two (2) credit hours).
| Code | Title | Hours |
|---|---|---|
| BE 668 | Translational Bioengineering teaching Practicum | 2 |
| or BE 692 | Bioengineering Clinical Rotation | |
| Biomedical Acoustics | ||
| LabVIEW for Bioengineers | ||
| Machine Learning in Python | ||
| Machine Learning in Medicine | ||
| Medical Image Computing | ||
| Computer Tools for Medical Image Analysis | ||
| Artificial Intelligence Techniques in Digital Pathology | ||
| Introduction to Tissue Engineering | ||
| Nanoscale Bioengineering: Application and Methodology of Nanobiomaterials in Bioengineering | ||
| Advanced Computer-Aided Design and Manufacturing for Bioengineers | ||
| Introduction to Artificial Intelligence in Bioengineering | ||
| Tissue and Molecular Biology Techniques Laboratory | ||
| Cardiovascular Dynamics | ||
| Biomechanical Computer Modeling and Simulation of Human Movement | ||
| Injury Biomechanics | ||
| Computational Methods for Medical Image Analysis | ||
| Artificial Intelligence and Radiomics | ||
| Advanced Biomaterials | ||
| Rehabilitation Engineering and Assistive Technology | ||
| Cellular Mechanobiology in Cancer | ||
| Artificial Organs | ||
| Modeling of Biological Phenomena | ||
| Fundamentals of Neuroscience | ||
| Molecular Neuroscience | ||
| Seminar on Developmental Neurobiology | ||
| Advanced Biochemistry I | ||
| Cancer Biology | ||
| Python and Data Analytics | ||
| Special Topics in Computer Science and Engineering | ||
| Design and Analysis of Computer Algorithms | ||
| Computer Graphics | ||
| Data Mining | ||
| Computer Vision | ||
| Data Mining with Linear Models | ||
| Introduction to Bioinformatics | ||
| Special Topics in Computer Science and Engineering | ||
| Digital Signal Processing | ||
| Digital Signal Processing Laboratory | ||
| Introduction to Biometrics | ||
| Microfabrications/MEMS Laboratory | ||
| Fundamentals of Autonomous Robots | ||
| Fundamentals of Autonomous Robots Lab | ||
| Deep Learning | ||
| Sampled-Data Control Systems | ||
| Introduction to Optimum Control | ||
| Research Design I | ||
| Research Design II | ||
| Strategic Entrepreneurship | ||
| Entrepreneurship Theory I | ||
| Entrepreneurship Theory II | ||
| Corporate Entrepreneurship and Innovation | ||
| Experimental Design in Engineering | ||
| Advanced Engineering Mathematics II | ||
| Mechatronics | ||
| Advanced Fluid Mechanics | ||
| Advanced Topics in Mechanical Engineering | ||
| Molecular Microbiology | ||
| Immunology | ||
| Methods and Analysis in the Biomedical Sciences | ||
| Topics in Advanced Microbiology | ||
| Craniofacial Osteology | ||
| Craniomaxillofacial Diagnostic Imaging | ||
| Advanced Oral Pathology | ||
| Data Mining I | ||
| Data Mining II | ||
| Introduction to Statistical Computing | ||
| Probability | ||
| Biostatistical Methods I | ||
| Multivariate Statistical Analysis | ||
| Categorical Data Analysis | ||
| Advanced Statistical Computing I | ||
| Advanced Human Cardiovascular Physiology | ||
