Biomedical and Chemical Engineering Doctor of Philosophy (Ph.D.) Degree

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The biomedical and chemical engineering Ph.D. program provides you with the knowledge, training, and expertise to tackle important problems in industry, academia, government, and health care.

Overview for Biomedical and Chemical Engineering Ph.D.

In the biomedical and chemical engineering Ph.D. program you will complete a number of classes in your first two years of study, including foundational courses with other engineering doctorate students, discipline-specific courses within biomedical and chemical engineering, and elective courses you select with your research advisor. You will complete a research thesis project with your faculty advisor in their lab and may have the opportunity to complete a complementary industrial co-op or internship. You will graduate from the program as a highly skilled researcher who is well positioned to be a leader in the next generation of engineers who will help tackle the challenging and complex problems facing our society.

Plan of Study

The curriculum for the biomedical and chemical engineering Ph.D. program provides the knowledge and skills to develop successful independent researchers.

Core Courses: Core courses, which are usually completed during the first two semesters of the program, serve as foundational preparation for elective courses. They develop your core competency skills for research, introduce the research landscape in biomedical and chemical engineering, and helping prepare you for the qualifying exam.

Discipline Concentration Elective Courses: The discipline concentration elective courses provide rigorous education in a field of research in biomedical and chemical engineering. Students may choose elective courses in consultation with the dissertation and research advisor, and from courses offered by the department of biomedical engineering and the department of chemical engineering.

Focus Area Elective Courses: Focus area elective courses provide the flexibility for you to engage in trans-disciplinary learning. In consultation with your dissertation and research advisor, you will select graduate level elective courses offered by any of the departments in the Kate Gleason College of Engineering. In addition, and subject to the program director’s approval, you may choose graduate courses offered by any of the RIT colleges.

Qualifying Exam: You will complete a qualifying exam at the end of your first year of study. The exam evaluates your aptitude, potential, and competency in conducting doctorate-level research. Through written documentation and a presentation of your work, you will critically review a recent peer-reviewed journal article in your field and propose a creative extension of the work.

Dissertation Proposal and Candidacy Exam: You will present and defend a dissertation proposal to your dissertation committee typically during your third year of study. The proposal provides the opportunity for you to elaborate on your research plans and to obtain feedback from your dissertation committee on the direction and approach of your research.

Research Review Meetings: Research review meetings provide comprehensive feedback regarding your dissertation research progress and expected outcomes prior to the defense of your full dissertation.

Dissertation Presentation and Defense: You will prepare an original, technically rigorous, and well-written dissertation that describes your research body of work and novel contributions that have resulted from your doctoral studies in biomedical and chemical engineering. You will present and defend your dissertation and its accompanying research to your dissertation committee.

Research Assistantships

Research assistantships are available to doctoral students. Learn more about the college’s research assistantship opportunities and how you can apply.

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Research

Please visit the research laboratory profiles on the biomedical engineering department and chemical engineering department websites for an overview of opportunities. Visit individual faculty profiles for a more complete list of research advisors in the program.

AWARE-AI NSF Research Traineeship Program

The AWARE-AI National Science Foundation Research Traineeship Program provides a unique opportunity to RIT's graduate students, who are poised to become future research leaders in developing responsible, human-aware AI technologies.

Students in the mechanical and industrial engineering doctorate program are eligible to apply for traineeships in the AWARE-AI NSF Research Traineeship (NRT) Program. Trainees experience convergent AI research guided by accomplished RIT faculty who work in cross-disciplinary research tracks. In addition to high-touch mentoring, students also engage in curated, career-advancement activities. Learn more about the benefits of the trainee program, including training opportunities, application requirements, and deadlines.

Research Assistantships

Research assistantships are available to doctoral students. Learn more about the college's research assistantship opportunities and how you can apply.

Careers and Internships

Internships

You may apply for internships in industry or at one of the national laboratories that align with your thesis research. Internships provide an opportunity for hands-on research experience, professional networking, and can serve to advance your thesis work. In addition, you may identify research opportunities at the National Labs Career Fair, an annual event hosted by RIT that brings representatives to campus from the United States’ federally-funded research and development labs.

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Curriculum for 2024-2025 for Biomedical and Chemical Engineering Ph.D.

Current Students: See Curriculum Requirements

View Printable Curriculum

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

Course Sem. Cr. Hrs.
First Year
BCEP-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. (This course is available to RIT degree-seeking graduate students.) Lecture 1 (Fall, Spring).
 2
BCEP-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 towards degree requirements. If the student enrolls cumulatively in more than 9 credits, the additional credits above 9 will not be counted towards the degree. Research 40 (Fall, Spring, Summer).
 3
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
 
Engineering Foundation Electives
 6
 
Discipline Concentration †
 6
Second Year
BCEP-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. (This course is available to RIT degree-seeking graduate students.) Lecture 1 (Fall, Spring).
 1
BCEP-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 towards degree requirements. If the student enrolls cumulatively in more than 9 credits, the additional credits above 9 will not be counted towards the degree. Research 40 (Fall, Spring, Summer).
 6
 
Discipline Concentration †
 3
 
Focus Area Electives ‡
 12
Third Year
BCEP-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 (Fall, Spring, Summer).
 21
Total Semester Credit Hours
66

* BCEP-795 Doctoral Seminar is taken three times, twice in the first year and once in the second year.

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

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

Electives

Engineering Foundation Electives

Course
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).
ENGR-707
Engineering Analysis
This course trains students to utilize mathematical techniques from an engineering perspective, and provides essential background for success in graduate level studies. An intensive review of linear and nonlinear ordinary differential equations and Laplace transforms is provided. Laplace transform methods are extended to boundary-value problems and applications to control theory are discussed. Problem solving efficiency is stressed, and to this end, the utility of various available techniques are contrasted. The frequency response of ordinary differential equations is discussed extensively. Applications of linear algebra are examined, including the use of eigenvalue analysis in the solution of linear systems and in multivariate optimization. An introduction to Fourier analysis is also provided. (This class is restricted to degree-seeking graduate students or those with permission from instructor.) Lecture 3 (Fall, Spring).
ENGR-709
Advanced Engineering Mathematics
Advanced Engineering Mathematics provides the foundations for complex functions, vector calculus and advanced linear algebra and its applications in analyzing and solving a variety of electrical engineering problems especially in the areas of control, circuit analysis, communication, and signal/image processing. Topics include: complex functions, complex integration, special matrices, vector spaces and subspaces, the nullspace, projection and subspaces, matrix factorization, eigenvalues and eigenvectors, matrix diagonalization, singular value decomposition (SVD), 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. (This class is restricted to degree-seeking graduate students or those with permission from instructor.) Lecture 3 (Fall, Spring).
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-257 or MATH-252 or MCEE-205 or STAT-205 or equivalent course or students in ISEE-MS, ENGMGT-MS, or MIE-PHD 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).

Admissions and Financial Aid

This program is available on-campus only.

Offered Admit Term(s) Application Deadline STEM Designated
Full‑time Fall December 15 priority deadline Yes

Full-time study is 9+ semester credit hours. International students requiring a visa to study at the RIT Rochester campus must study full‑time.

Application Details

To be considered for admission to the Biomedical and Chemical Engineering Ph.D. program, candidates must fulfill the following requirements:

  • Learn tips to apply for a doctoral program and then complete a graduate application.
  • Submit copies of official transcript(s) (in English) of all previously completed undergraduate and graduate course work, including any transfer credit earned.
  • Hold a baccalaureate degree (or US equivalent) from an accredited university or college. A minimum cumulative GPA of 3.0 (or equivalent) is recommended.
  • Submit a current resume or curriculum vitae.
  • Submit a statement of purpose for research which will allow the Admissions Committee to learn the most about you as a prospective researcher.
  • Submit two letters of recommendation.
  • Entrance exam requirements: GRE optional but recommended. No minimum score requirement.
  • Submit English language test scores (TOEFL, IELTS, PTE Academic), if required. Details are below.

English Language Test Scores

International applicants whose native language is not English must submit one of the following official English language test scores. Some international applicants may be considered for an English test requirement waiver.

TOEFL IELTS PTE Academic
94 7.0 66

International students below the minimum requirement may be considered for conditional admission. Each program requires balanced sub-scores when determining an applicant’s need for additional English language courses.

How to Apply Start or Manage Your Application

Cost and Financial Aid

An RIT graduate degree is an investment with lifelong returns. Ph.D. students typically receive full tuition and an RIT Graduate Assistantship that will consist of a research assistantship (stipend) or a teaching assistantship (salary).

Resources

Access resources for students including student manual and research resources.

Research Resources

Contact

Admissions Contact
  • Laura Watts
  • Senior Associate Director
  • Office of Graduate and Part-Time Enrollment Services
  • Enrollment Management
  • 585‑475‑4901
  • Laura.Watts@rit.edu
Program Contact