Biomedical and Chemical Engineering Ph.D.

Biomedical and Chemical Engineering, Ph.D. degree, typical course sequence

Course Sem. Cr. Hrs.
First Year
ENGR-701
Inter-disciplinary Research Methods
This course emphasizes collaboration in modern research environment and consists of five modules. Students will introduced to the concepts of inter-disciplinary and trans-disciplinary research conducted from both a scientific and an engineering perspective. Students will learn how to write a dissertation proposal, statement of work, timeline for their program of study and the elements of an effective literature review. Students will develop skills related to reviewing and annotating technical papers, conducting a literature search and proper citation. Students will demonstrate an understanding of (a) ethics as it relates to the responsible conduct of research, (b) ethical responsibility in the context of the engineering professions, (c) ethics as it relates to authorship and plagiarism, (d) basic criteria for ethical decision making and (e) identify professional standards and code of ethics relevant to their discipline. Students demonstrate an ability to identify and explain the potential benefits of their research discoveries to a range of stakeholders, including policy makers and the general public. Lecture 3 (Fall).
3
ENGR-702
Translating Discovery into Practice
This course provides graduate students with the professional skills needed by PhD graduates within their major research focus area to move the results of their research from the lab into practice. Students will demonstrate a strong contextual understanding for their research efforts. Students will learn professional skills related to Teamwork; Innovation, Entrepreneurship and Commercialization; Research Management; Policy and Societal Context; and Technical Writing. (This class is restricted to degree-seeking graduate students or those with permission from instructor.) Lecture 3 (Spring).
3
ENGR-795
Doctoral Seminar
This seminar course presents topics of contemporary interest to graduate students enrolled in the program. Presentations include off campus speakers, and assistance with progressing on your research. Selected students and faculty may make presentations on current research under way in the department. All doctoral engineering students enrolled full time are required to attend each semester they are on campus. (Graduate standing in a technical discipline) (This class is restricted to degree-seeking graduate students or those with permission from instructor.) Seminar 1 (Fall, Spring).
2
ENGR-892
Graduate Research
Doctoral-level research by the candidate on an appropriate topic as arranged between the candidate and the research advisor. Students may count a maximum of 9 credits of ENGR-892 towards degree requirements. If the student enrolls cumulatively in more than 9 credits of ENGR-892, the additional credits above 9 will not be counted towards the degree. Research 3 (Fall, Spring, Summer).
3
 
Engineering Foundation 1, 2*
6
 
Discipline Concentration 1, 2†
6
Second Year
ENGR-795
Doctoral Seminar
This seminar course presents topics of contemporary interest to graduate students enrolled in the program. Presentations include off campus speakers, and assistance with progressing on your research. Selected students and faculty may make presentations on current research under way in the department. All doctoral engineering students enrolled full time are required to attend each semester they are on campus. (Graduate standing in a technical discipline) (This class is restricted to degree-seeking graduate students or those with permission from instructor.) Seminar 1 (Fall, Spring).
1
ENGR-892
Graduate Research
Doctoral-level research by the candidate on an appropriate topic as arranged between the candidate and the research advisor. Students may count a maximum of 9 credits of ENGR-892 towards degree requirements. If the student enrolls cumulatively in more than 9 credits of ENGR-892, the additional credits above 9 will not be counted towards the degree. Research 3 (Fall, Spring, Summer).
6
 
Discipline Concentration 3†
3
 
Focus Area Elective 1, 2, 3, 4‡
12
Third Year
ENGR-890
Dissertation and Research
Doctoral-level research by the candidate on an appropriate topic as arranged between the candidate and the research advisor. Students must successfully pass the PhD Candidacy examination prior to enrolling in this course Research 3 (Fall, Spring, Summer).
21
Total Semester Credit Hours
66

*Engineering Foundation Electives:

BIME-750
Statistical Analysis and Modeling of Biomedical Data
This course will expose student to the basic properties of data collected from biological systems and issues involved in the statistical analysis of such data. Specifically, this course will review the motivations and rationale behind conventional regression models, issues that arise in applying these methods to biological data, and specific extensions of these methods required to obtain meaningful results. Specific examples of these approaches and their application will be given at different levels of biology. The analysis of such problems will require the use of advanced regression techniques directed at resolving the partial confounding that is typical of living (closed loop regulated) systems, applied under statistical software packages (e.g., spreadsheets, graphing, Matlab, SPSS, Simca). (This class is restricted to degree-seeking graduate students or those with permission from instructor.) Lab 3 (Biannual).
CHME-709
Advanced Engineering Mathematics
The course begins with a pertinent review of linear and nonlinear ordinary differential equations and Laplace transforms and their applications to solving engineering problems. It then continues with an in-depth study of vector calculus, complex analysis/integration, and partial differential equations; and their applications in analyzing and solving a variety of engineering problems. Topics include: ordinary and partial differential equations, Laplace transforms, vector calculus, complex functions/analysis, complex integration. Chemical engineering applications will be discussed throughout the course. (Prerequisites: Graduate standing in Chemical Engineering.) Lecture 3 (Fall).
EEEE-707
Engineering Analysis
The course trains students to utilize mathematical techniques from an engineering perspective, and provides essential background for success in graduate level studies. The course begins with a pertinent review of matrices, transformations, partitions, determinants and various techniques to solve linear equations. It then transitions to linear vector spaces, basis definitions, normed and inner vector spaces, orthogonality, eigenvalues/eigenvectors, diagonalization, state space solutions and optimization. Applications of linear algebra to engineering problems are examined throughout the course. Topics include: Matrix algebra and elementary matrix operations, special matrices, determinants, matrix inversion, null and column spaces, linear vector spaces and subspaces, span, basis/change of basis, normed and inner vector spaces, projections, Gram-Schmidt/QR factorizations, eigenvalues and eigenvectors, matrix diagonalization, Jordan canonical forms, singular value decomposition, functions of matrices, matrix polynomials and Cayley-Hamilton theorem, state-space modeling, optimization techniques, least squares technique, total least squares, and numerical techniques. Electrical engineering applications will be discussed throughout the course. (Prerequisites: This course is restricted to graduate students in the EEEE-MS, EEEE-BS/MS program.) Lecture 3 (Fall, Spring).
EEEE-709
Advanced Engineering Mathematics
The course begins with a pertinent review of linear and nonlinear ordinary differential equations and Laplace transforms and their applications to solving engineering problems. It then continues with an in-depth study of vector calculus, complex analysis/integration, and partial differential equations; and their applications in analyzing and solving a variety of engineering problems especially in the areas of control, circuit analysis, communication, and signal/image processing. Topics include: ordinary and partial differential equations, Laplace transforms, vector calculus, complex functions/analysis, complex integration, and numerical techniques. Electrical engineering applications will be discussed throughout the course. (This class is restricted to degree-seeking graduate students or those with permission from instructor.) Lecture 3 (Fall, Spring, Summer).
ISEE-760
Design of Experiments
This course presents an in-depth study of the primary concepts of experimental design. Its applied approach uses theoretical tools acquired in other mathematics and statistics courses. Emphasis is placed on the role of replication and randomization in experimentation. Numerous designs and design strategies are reviewed and implications on data analysis are discussed. Topics include: consideration of type 1 and type 2 errors in experimentation, sample size determination, completely randomized designs, randomized complete block designs, blocking and confounding in experiments, Latin square and Graeco Latin square designs, general factorial designs, the 2k factorial design system, the 3k factorial design system, fractional factorial designs, Taguchi experimentation. (Prerequisites: ISEE-325 or STAT-252 or MATH-252 or equivalent course or students in ISEE-MS, ISEE-ME, SUSTAIN-MS, SUSTAIN-ME or ENGMGT-ME programs.) Lecture 3 (Spring).
MATH-655
Biostatistics
This course is an introduction to the probabilistic models and statistical techniques used in the analysis of biological and medical data. Topics include univariate and multivariate summary techniques, one and two sample parametric and nonparametric inference, censoring, one and two way analysis of variance, and multiple and logistic regression analysis. (This class is restricted to graduate students in COS, KGCOE, GCCIS, CHST or CLA.) Lecture 3 (Spring).

† Discipline Concentration: Any graduate level course offered by the departments of biomedical or chemical engineering, exclusive of capstones.

‡ Focus Area Elective: Any graduate level course offered by the Kate Gleason College of Engineering, exclusive of capstones.