For admission information, see Graduate Programs Admission.
The following introductory information is based on 2022-23 program requirements for UCLA graduate degrees. Complete program requirements are available at Program Requirements for UCLA Graduate Degrees. Students are subject to the detailed degree requirements as published in program requirements for the year in which they enter the program.
The Bioengineering Department offers Master of Science (MS) and Doctor of Philosophy (PhD) degrees in Bioengineering.
A minimum of 13 courses (44 units) is required.
For the comprehensive plan, at least 11 courses must be from the 200 series, three of which must be Bioengineering 299 courses. Students must also take one 495 course. One 100-series course may be applied toward the total course and unit requirement. No units of 500-series courses may be applied toward the minimum course requirements.
For the thesis plan, at least 10 of the 13 courses must be from the 200 series, three of which must be Bioengineering 299 courses. Students must also take two 598 courses involving work on the thesis and one 495 course.
To remain in good academic standing, MS students must maintain an overall grade-point average of 3.0 and a grade-point average of 3.0 in graduate courses.
The comprehensive examination plan is available in all fields, and requirements vary for each field. Specific details are available from the graduate adviser. Students who fail the examination may repeat it once only, subject to the approval of the faculty examination committee. Students who fail the examination twice are not permitted to submit a thesis and are subject to termination.
Every master’s degree thesis plan requires the completion of an approved thesis that demonstrates student ability to perform original, independent research. New students who select this plan are expected to submit the name of the thesis adviser to the graduate adviser by the end of their first term in residence. The thesis adviser serves as chair of the thesis committee.
A research thesis (8 units of Bioengineering 598) is to be written on a bioengineering topic approved by the thesis adviser. The thesis committee consists of the thesis adviser and two other qualified faculty members who are selected from a current list of designated members for the graduate program.
To complete the PhD degree, all students must fulfill minimum University requirements. Students must pass the University Oral Qualifying Examination and final oral examination, and complete the courses in Group I and Group II under Fields of Study below. Also see Course Requirements under Bioengineering MS Students must maintain a grade-point average of 3.25 or better in all courses.
Academic Senate regulations require all doctoral students to complete and pass University written and oral qualifying examinations prior to doctoral advancement to candidacy. Under Senate regulations the University Oral Qualifying Examination is open only to students and appointed members of their doctoral committees. In addition to University requirements, some graduate programs have other precandidacy examination requirements. What follows are the requirements for this doctoral program.
To remain in good standing in the program, PhD students are expected to take the University Oral Qualifying Examination within six academic quarters and two summer quarters (i.e., two years) following matriculation. The nature and content of the examination are at the discretion of the doctoral committee, but ordinarily include a broad inquiry into the student’s preparation for research. The doctoral committee also reviews the prospectus of the dissertation, the written component of the qualifying examination, prior to the oral qualifying examination.
A doctoral committee consists of a minimum of four qualified UCLA faculty members. All committee nominations and reconstitutions adhere to the Minimum Standards for Doctoral Committee Constitution.
A final oral examination (defense of the dissertation) is required of all students.
The biomedical data sciences (BDS) field trains students to be experts in the use of computational, statistical, and machine learning tools for solving biomedical problems. BDS is intended for science and engineering students interested in how data science tools can operate alongside other areas of bioengineering to solve problems in areas including pattern recognition, prediction, control, measurement, and visualization. Students are trained in the algorithmic and statistical fundamentals of the field. Directed interdisciplinary training prepare students to be practitioners in the application of data science to analyze clinical imaging, molecular and cellular systems, medical devices, electronic health record data, and the many other areas of biomedicine that routinely generate data. In parallel to learning fundamentals, students develop expertise in these application areas, providing them additional expertise in real-world problem solving. In total, this area fosters the development of students who go on to become data scientists with the unique ability to actively interface with practitioners in other areas of bioengineering and medicine.
The biomedical devices and instrumentation (BDMI) field is designed to train bioengineers interested in the applications and development of instrumentation used in medicine and biotechnology. Examples include the use of lasers in surgery and diagnostics, new microelectrical machines for surgery, sensors for detecting and monitoring of disease, microfluidic systems for cell-based diagnostics, new tool development for basic and applied life sciences research, and controlled drug delivery devices. The principles underlying each instrument and specific clinical or biological needs are emphasized. Graduates are targeted principally for employment in academia; government research laboratories; and the biotechnology, medical devices, and biomedical industries.
The biomedical imaging (BI) field consists of the following two subfields: biomedical imaging hardware development (BIHD) and biomedical signal and image processing (BSIP).
The BIHD subfield prepares students for a career in developing imaging hardware for medical diagnosis and intervention applications. Students learn the physical basis of biomedical imaging modalities such as optical imaging, CT, and MRI. The students will also be trained with hands-on experiences to build state-of-the-art imaging devices and test their performance in real-world medical imaging scenarios. Through the structured curriculum and lab activities, the students experience the excitement of cutting-edge hardware research, hone skills in analytical thinking and communications, and gain knowledge of imaging techniques that are used in the biomedical field.
The BSIP subfield prepares students for a career in the acquisition and analysis of biomedical signals; and enables students to apply quantitative methods applied to extract meaningful information for both clinical and research applications. The BSIP program is premised on the fact that a core set of mathematical and statistical methods are held in common across signal acquisition and imaging modalities and across data analyses regardless of their dimensionality. These include signal transduction, characterization and analysis of noise, transform analysis, feature extraction from time series or images, quantitative image processing and imaging physics. Students in the BSIP program have the opportunity to focus their work over a broad range of modalities including electrophysiology; optical imaging methods; MRI, CT, PET, and other tomographic devices; and/or on the extraction of image features such as organ morphometry or neurofunctional signals, and detailed anatomic/functional feature extraction. The career opportunities for BSIP trainees include medical instrumentation, engineering positions in medical imaging, and research in the application of advanced engineering skills to the study of anatomy and function.
The molecular, cellular, and tissue engineering (MCTE) field covers novel therapeutic development across all biological length scales from molecules to cells to tissues. At the molecular and cellular levels, this research area encompasses the engineering of biomaterials, ligands, enzymes, protein-protein interactions, intracellular trafficking, biological signal transduction, genetic regulation, cellular metabolism, drug delivery vehicles, and cell-cell interactions, as well as the development of chemical/biological tools to achieve this.
At the tissue level, the field encompasses two subfields—biomaterials and tissue engineering. The properties of bone, muscles, and tissues, the replacement of natural materials with artificial compatible and functional materials such as polymers, composites, ceramics, and metals, and the complex interactions between implants and the body are studied at the tissue level. The research emphasis is on the fundamental basis for diagnosis, disease treatment, and redesign of molecular, cellular, and tissue functions. In addition to quantitative experiments required to obtain spatial and temporal information, quantitative and integrative modeling approaches at the molecular, cellular, and tissue levels are also included within this field. Although some of the research remains exclusively at one length scale, research that bridges any two or all three length scales is also an integral part of this field. Graduates are targeted principally for employment in academia, government research laboratories, and the biotechnology, pharmaceutical, and biomedical industries.
The neuroengineering (NE) field is designed to enable students with a background in biological sciences to develop and execute projects that make use of state-of-the-art technology, including microelectromechanical systems (MEMS), signal processing, and photonics. Students with a background in engineering develop and execute projects that address problems that have a neuroscientific base, including locomotion and pattern generation, central control of movement, and the processing of sensory information. Trainees develop the capacity for the multidisciplinary teamwork, in intellectually and socially diverse settings, that is necessary for new scientific insights and dramatic technological progress in the twenty-first century. Students take a curriculum designed to encourage cross-fertilization of neuroscience and engineering. The goal is for neuroscientists and engineers to speak each others’ language and move comfortably among the intellectual domains of the two fields.