summer research training program in biomedical big data science

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UCLA Graduate Programs

Program Requirements for Bioinformatics (Medical Informatics)

Applicable only to students admitted during the 2024-2025 academic year.

Bioinformatics

Interdepartmental Program College of Letters and Science

Graduate Degrees

The Medical Informatics Program offers the Master of Science (M.S.) and Doctor of Philosophy (Ph.D.) degrees in Medical Informatics.

Admissions Requirements

Master’s Degree

All academic affairs for graduate students in the program are directed by the program’s faculty graduate adviser, who is assisted by staff in the Graduate Student Affairs Office. Upon matriculation, students are assigned a three-faculty guidance committee by the faculty graduate adviser.

The chair of the guidance committee acts as the provisional adviser until a permanent adviser is selected. Provisional advisers are not committed to supervise examination or thesis work and students are not committed to the provisional adviser. Students select a permanent adviser before establishing a comprehensive examination or thesis committee.

Areas of Study

This area of study exposes students to foundational concepts in medical informatics, providing a background in clinical data, big data management, and analyses of new and emergent data utilized to guide biomedical research and healthcare. Study comprises of an introduction to computational methods, clinical and biomedical knowledge representation, and exposure to core informatics topics.

Foreign Language Requirement

Course Requirements

Students must be enrolled full time and complete 40 units (11 courses) of graduate (200 or 500 series) course work for the master’s degree. All courses must be taken for a letter grade, unless offered on S/U grading basis only.

Students must complete all of the following: (1) eight core courses (30 units): Bioengineering 220, 223A, 223B, one course from BE 224A or Bioinformatics M222 through M226, BE 224B, BE M226, BE M227, and BE M228; (2) eight units of Bioinformatics 596; and (3) two units of 200-level seminar or journal club courses approved by the program.

Teaching Experience

Not required.

Field Experience

Capstone Plan

The master’s capstone is an individual project in the format of a written report resulting from a research project. The report should describe the results of the student’s investigation of a problem in the area of medical informatics under the supervision of a faculty member in the program, who approves the subject and plan of the project, as well as reading and approving the completed report. While the problem may be one of only limited scope, the report must exhibit a satisfactory style, organization, and depth of understanding of the subject. A student should normally start to plan the project at least one quarter before the award of the M.S. degree is expected. The advisory committee evaluates and grades the written report as not pass or M.S. pass and forwards the results to the faculty graduate adviser. Students who do not pass the evaluation are permitted one additional opportunity to pass, which must be submitted to and graded by the advisory  committee by the end of the 6th quarter.

The capstone plan is available for students in the Medical Informatics field. However, students in Computational & Systems Biology major are required to follow the Thesis Plan only.

Thesis Plan

Every master’s degree thesis plan requires the completion of an approved thesis that demonstrates the student’s ability to perform original, independent research.

Students must choose a permanent faculty adviser and submit a thesis proposal by the end of the third quarter of study. The proposal must be approved by the permanent adviser who served as the thesis adviser. The thesis is evaluated by a three-person committee that is nominated by the program and appointed by the Division of Graduate Education. Students must present the thesis in a public seminar.

Time-to-Degree

Normative time-to-degree for all fields is five quarters.

Doctoral Degree

The Medical Informatics Advising Committee, chaired by the Faculty Graduate Advisor, advises students during the first year and is available to students throughout their tenure of their study.

Upon entering their second year in the program, students will select a mentor who will serve as their dissertation chair, research advisor, and primary graduate advisor. Together the student and the mentor will convene a doctoral committee who will guide the student throughout their research, the University Oral Qualifying Exam, Doctoral Dissertation Defense, and will approve the final dissertation.

Individual Development Plan: Beginning with a mandatory training workshop in the first quarter of graduate study, students are required to generate an Individual Development Plan via myIDP Website: http://myidp.sciencecareers.org/ in order to map out their academic and professional development goals throughout graduate school. The myIDP must be updated annually, and the resulting printed summary discussed with and signed by (Year 1) the student’s advising committee member, or (Years 2-5) thesis adviser, and then turned in to the Graduate Student Affairs Office to be placed in the student’s academic file each year by June 1.

Annual Committee Meetings: Beginning one year after advancement to doctoral candidacy, and in each year thereafter until completion of the degree program, students are required to meet annually with their doctoral committee. At each meeting, students give a brief, 30-minute oral presentation of their dissertation research progress to their committee. The purpose of the meeting is to monitor the student’s progress, identify difficulties that may occur as the student progresses toward successful completion of the dissertation and, if necessary, approve changes in the  dissertation project. The presentation is not an examination.

Annual Progress Report: All students are required to submit a brief report (a one-page form is provided) of their time-to-degree progress and research activities indicating the principal research undertaken and any important results, research plans for the next year, conferences attended, seminars given, and publications appearing or manuscripts in preparation. Annual Progress report must be submitted to the Bioinformatics IDP Student Affairs Office for review by the Program Director.

Major Fields or Subdisciplines

These fields include computer science, translational bioinformatics, imaging informatics, public health informatics, and social medicine.

Students are required to enroll full-time in a minimum of 12 units each quarter. In addition to basic course requirements, all students are required to enroll in Bioinformatics 596 or 599 each quarter.

Students who have gaps in their previous training may take, with their thesis adviser’s approval, appropriate undergraduate courses. For example, students without statistical background are recommended to take STATS 100B (Introduction to Mathematics Statistics) in their 1st year. Students without a Computer Science background are recommended to take COM SCI 180  Introduction to Algorithms and Complexity), COM SCI 145 (Introduction to Data Mining), COM SCI 146 (Introduction to Machine Learning), or COM SCI 148 (Introduction to Data Science). However, these courses may not be applied toward the required course work for the doctoral degree.

Students must complete all of the following: (1) eight core courses (30 units) Bioengineering 220, 223A, 223B, one course from BE 224A or Bioinformatics M223 or M226, BE 224B, BE M226, BE M227, and BE M228; (2) MIMG C234; (3) eight units of Bioinformatics 596; (4) four units of 200-level seminar or journal club courses approved by the program; and (5) six electives, chosen from the following list: Bioinformatics M223, M226; Biomathematics 210, M230, M281, M282; Biostatistics 213, M232, M234, M235, 241, 276; Computer Science 240A, 240B, 241B, 245, 246, 247, 262A, M262C, 262Z, 263A, 265A, M268, M276A; Electrical and Computer Engineering 206, 210A, 210B, 211A, M217, 219; Information Studies 228, 246, 272, 277; Linguistics 218, 232; Neuroscience CM272; Physics in Biology and Medicine 210, 214. M248; Statistics 221, M231A, 231B, M232A, M232B, 238, M241, M243, M250, 256. Please note: other elective courses can be taken with the agreement of the Home Area Director and the student’s PI/faculty mentor. Courses must be taken for a letter grade, unless offered on S/U grading basis only.

Written and Oral Qualifying Examinations

Academic Senate regulations require all doctoral students to complete and pass university written and oral qualifying examinations prior to doctoral advancement to candidacy. Also, under Senate regulations, the University Oral Qualifying Examination is open only to the student and appointed members of the doctoral committee. In addition to university requirements, some graduate programs have other pre-candidacy examination requirements. What follows in this section is how students are required to fulfill all of these requirements for this doctoral program.

All committee nominations and reconstitutions adhere to the  Minimum Standards for Doctoral Committee Constitution .

Doctoral students must complete the core courses described above before they are permitted to take the written and oral qualifying examinations. Students are required to pass a written qualifying examination that consists of a research proposal outside of their dissertation topic and the University Oral Qualifying Examination in which they defend their dissertation research proposal before their doctoral committee. Students are expected to complete the written examination in the summer following the first year and the oral qualifying examination by the end of fall quarter of the third year. The written qualifying examination must be passed before the University Oral Qualifying Examination can be taken.

During their first year, doctoral students perform laboratory rotations with program faculty whose research is of interest to them and select a dissertation adviser from the program faculty inside list by the end of their third quarter of enrollment. By the end of their second spring quarter, students must select a doctoral committee that is approved by the program chair and the Division of Graduate Education.

Written Qualifying Examination

The Written Qualifying Examination (WQE) must take place in the summer following the first year of doctoral study. In order to be eligible to take the WQE, students must have achieved at least two passing lab rotation evaluations, as well as at least a B average in all course work. Students are expected to formulate a testable research question and answer it, by carrying out a small, well-defined and focused project over a fixed one-month period. It must include the development of novel bioinformatic methodology. The topic and methodologies are to be selected by the student. The topic requires advance approval by the faculty committee, and may not be a project from a previous course, a rotation project, a project related to the student’s prior research experience, an anticipated dissertation research topic, or an active or anticipated research project in the laboratory of the student’s mentor. The WQE must be the student’s own ideas and work exclusively. Students are expected to complete a WQE paper of publication quality (except for originality), with a maximum length of 10 pages, single-spaced, excluding figures and references. This paper is submitted to the Student Affairs Office and graded by a faculty committee on a pass or no-pass basis. Students who do not pass the examination are permitted one additional opportunity to pass, which must be submitted to and graded by the faculty committee no later than the end of the summer of the first year.

Oral Qualifying Examination

The University Oral Qualifying Examination must be completed and passed by the end of the fall quarter of the third year. Students prepare a written description of the scientific background of their proposed dissertation research project, the specific aims of the project, preliminary findings, and proposed bioinformatic approaches for addressing the specific aims. This dissertation proposal must be written following an NIH research grant application format and be at least six pages, single spaced and excluding references, and is submitted to the students’ doctoral committee at least 10 days in advance of the examination. Exclusive of their doctoral committee members, students are free to consult with their dissertation adviser, or other individuals in  formulating the proposed research. The examination consists of an oral presentation of the proposal by the student to the committee. The student’s oral presentation and examination are expected to demonstrate: (1) a scholarly understanding of the background of the research proposal; (2) well-designed and testable aims; (3) a critical understanding of the bioinformatic, mathematical or statistical methodologies to be employed in the proposed research; and (4) an understanding of potential bioinformatic outcomes and their interpretation. This examination is graded Pass, Conditional Pass, or Fail. If the doctoral committee decides that the examination reflects performance below the expected mastery of graduate-level content, the committee may vote to give the student a Conditional Pass. A student who receives a Conditional Pass will be required to modify or re-write their research proposal, so as to bring it up to required standard. In the case of a Conditional Pass, the student will be permitted to seek the advice of their committee in modifying or re-writing the proposal. Any required re-write or modification will be submitted to, and reviewed by the doctoral committee. A second oral presentation is not necessary unless the doctoral committee requires so. The signed Report on the Oral Qualifying Examination & Request for Advancement to Candidacy will be retained in the Graduate Student Affairs Office until the student has satisfied the doctoral committee’s request for revision or re-write. Students are allowed only one chance to revise or re-write their proposal.

Advancement to Candidacy

Students are advanced to candidacy upon successful completion of the written and oral qualifying examinations.

Doctoral Dissertation

Every doctoral degree program requires the completion of an approved dissertation that demonstrates the student’s ability to perform original, independent research and constitutes a distinct contribution to knowledge in the principal field of study.

Final Oral Examination (Defense of the Dissertation)

Required for all students in the program.

Students are expected to complete the written qualifying examination in the summer following the first year of study and the University Oral Qualifying Examination by the end of fall quarter of the third year. Normative time-to-degree is five years (15 quarters).

Academic Disqualification and Appeal of Disqualification

University Policy

A student who fails to meet the above requirements may be recommended for academic disqualification from graduate study. A graduate student may be disqualified from continuing in the graduate program for a variety of reasons. The most common is failure to maintain the minimum cumulative grade point average (3.00) required by the Academic Senate to remain in good standing (some programs require a higher grade point average). Other examples include failure of examinations, lack of timely progress toward the degree and poor performance in core courses. Probationary students (those with cumulative grade point averages below 3.00) are subject to immediate dismissal upon the recommendation of their department. University guidelines governing academic disqualification of graduate students, including the appeal procedure, are outlined in Standards and Procedures for Graduate Study at UCLA .

Special Departmental or Program Policy

Students must receive at least a grade of B- in core courses or repeat the course. Students who received three grades of B- or lower in core courses, who fail all or part of the written or oral qualifying examinations twice, or who fail to maintain minimum progress may be recommended for academic disqualification by vote of the entire interdepartmental program committee. Failure to identify and maintain a thesis adviser is a basis for recommendation for academic disqualification. Students may appeal a recommendation for academic disqualification in writing to the interdepartmental program committee, and may personally present additional or mitigating information to the committee, in person or in writing.

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Mount Sinai Center for Bioinformatics: Summer Research Training Program in Biomedical Big Data Science

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PROGRAM ICONS

Summer Research Opportunity Program

Biomedical data science summer research may 28 – august 3, 2024, applications for summer 2024 : apply here.

The summer research program in Biomedical Data Science (BDS) gives undergraduate students (enrolled in Bachelor’s or Associate’s degree programs) the opportunity to explore careers in biostatistics, bioinformatics, and biomedical big data by working closely with faculty and staff mentors. Such an experience is ideal for students with strength in mathematics and computer sciences who enjoy working with computers and numbers and wish to apply their skills to solving real world problems in biomedical research.  There is a wide variety of research activities, including brain image analysis, clinical trials, electronic health records, epidemiology, genomics, experimental design and analysis of laboratory studies.

Financial Support

The BDS program is designed to be accessible to students who might not otherwise have this kind of research opportunity. There is no cost for program participation. In addition, a stipend is provided to each student, and housing and travel costs are covered. Underrepresented minority, low-income, and first-generation college students are strongly encouraged to apply, as are students from smaller institutions without broad research facilities.

Eligibility

• Strong interest in learning about biomedical data science
• Undergraduate (bachelor’s or associate’s degree) student status for Fall 2024
• Applicants must be U.S. citizens or permanent residents enrolled in an accredited college/university, majoring in either a quantitative science or in biology, and have successfully completed at least one year of calculus.
• Preference will be given to students who will have completed their junior year and who have a cumulative grade point average of at least 3.0.

A primary objective for our summer program is providing research experience to students who wouldn’t otherwise have the opportunity. We encourage applications from all eligible undergraduate students, examples of student groups that particularly benefit from this program include:

• Students who attend small colleges with limited research resources
• Identifying as historically underrepresented
• Low income background
• First in the family to attend college

Participants in the 2021 program worked as a team on a new the new Genomic Variant Interpretation project.  Read about our 2021 Program

UW STEM Diversity Network

To learn more about our graduate, certificate and summer programs and application procedures contact the administrative program director:

Shelley Maxted [email protected]

Summer Research Program in Biomedical Informatics and Health Data Science

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Provides high-school and college undergraduate students with fundamental knowledge, hands-on skills, and research experience in biomedical informatics and health data science

The Columbia Department of Biomedical Informatics (DBMI) summer research program provides high-school and college undergraduate students from a wide range of backgrounds (biology, psychology, engineering, computer science, applied mathematics, statistics, etc.) with fundamental knowledge, hands-on skills, and research experience in biomedical informatics and health data science.

The fellowship has two goals: (1) to promote biomedical informatics and health data science as a career choice for young scientist in training; and (2) to promote diversity in higher education and biomedical informatics and health data science by engaging students from traditionally underrepresented minority groups and creating an inclusive learning environment.

At the end of the six week program, fellows will have gained computing and research skills, familiarity with the fields of informatics and health data science, experience with real-world, massive health data-sets from electronic health records and the data acumen that comes with handling such data-sets, along with understanding of the complex ethical and fairness questions inherent to biomedical informatics and health data science research.

Dates & Deadlines

Mount Sinai Health System

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Virtual Symposium for the 2023 Summer Research Training Program in Biomedical Big Data Science

Thursday, August 10, 2023 10am to 12:15pm

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About this Event

Please join us on Thursday, August 10th at 10:00 AM ET for the virtual symposium featuring the Ma'ayan Laboratory's undergraduate trainees in the 2023 Summer Research Training Program in Biomedical Big Data Science. 

This nationally acclaimed summer program for undergraduate students is a ten-week research intensive training program. The trainees in the program carry out cutting-edge research projects aimed at solving data-intensive biomedical problems with computational methods. The faculty-mentored independent research projects are in the following areas: data harmonization, machine learning, cloud computing, and dynamic interactive data visualization, and are applied to datasets from cancer, diabetes, and aging. 

All staff, faculty, and students are welcome.

Event Details

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Registration

Please register in advance for the virtual symposium. After registering, you will receive a confirmation email containing information about joining the Zoom webinar.

Presenter(s)

The Ma'ayan Lab Undergraduate Research Fellows in the 2023 Summer Research Training Program in Biomedical Big Data Science

Dial-In Information

Zoom Registration Link  

Biomedical Big Data Training Program at UC Berkeley

Project concluded in 2021.

The Biomedical Big Data Training Program (BBD) at UC Berkeley officially concluded in 2021.

Nominations

Seminar archive.

The NIH-funded Biomedical Big Data Training Program at UC Berkeley responds to the urgent need for advances in data science so that the next generation of scientists has the necessary skills for leveraging the unprecedented and ever-increasing quantity and speed of biomedical information. Big data hold the promise for achieving new understandings of the mechanisms of health and disease, revolutionizing the biomedical sciences, making the grand challenge of Precision Medicine a reality, and paving the way for more effective policies and interventions at the community and population levels. These breakthroughs require highly trained researchers who are proficient in biomedical big data science and have advanced skills at collaborating effectively across traditional disciplinary boundaries.

"The ability to harvest the wealth of information contained in biomedical Big Data will advance our understanding of human health and disease; however, lack of appropriate tools, poor data accessibility, and insufficient training, are major impediments to rapid translational impact. To meet this challenge, the National Institutes of Health (NIH) launched the Big Data to Knowledge (BD2K) initiative in 2012. BD2K is a trans-NIH initiative established to enable biomedical research as a digital research enterprise, to facilitate discovery and support new knowledge, and to maximize community engagement." -​ https://datascience.nih.gov/bd2k/about

Beginning in the Fall of 2016, with proposed funding for five years, this training grant will support 6 trainees per program year. We anticipate further extending the reach of our program by admitting up to 2 additional students on alternative support, thus benefitting 8 students per year. The 25 participating faculty have extensive experience with biomedical applications and expertise in biostatistics, causal inference, machine learning, the development of big data tools, and scalable computing. Together, they span 8 departments/programs:

• Biostatistics
• Computational Biology
• Computer Science
• Epidemiology
• Integrative Biology
• Molecular & Cell Biology
• Neuroscience

We will recruit participants from Ph.D. students in their first or second year of study in any/all of these departments. Those accepted into the program will participate in an intensive year of training courses, seminars, and workshops, beginning with introductory seminars in late summer and ending with a capstone project by each participant in the spring. Specialized training will focus on three pillars:

• Translation of biomedical and experimental knowledge and scientific questions of interest into formal, realistic problems of causal and statistical estimation
• Scalable big data computing
• Targeted machine learning with causal and statistical inference

Activities will include courses in machine learning, targeted learning, statistical programming, and big data computing, as well as workshops led by the Berkeley Data Science Institute, Statistical Computing Facility, and Berkeley Research Computing. The capstone course will involve a collaborative project in biomedical science involving the integrated and combined application of skills acquired by the trainees in the three foundational areas. Trainees will also benefit from group seminars, retreats, and interdisciplinary meetings that build a core identity with the cadre and the program. This program dovetails with several data science and precision medicine initiatives at UC Berkeley and comes at an ideal time to influence how data science is taught to all graduate students, focusing on biomedical research across campus.

Lead Principle Investigator and Director

Mark van der Laan Ph.D., Professor of Biostatistics and Statistics

[email protected]

Co-Director

Alan Hubbard Ph.D., Professor and Division Head of Biostatistics

[email protected]

Program Coordinator

Lucas Carlton

[email protected]

(510) 643 0238

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Big Data Summer Institute - A SIBS Program

Transforming analytical learning in the era of big data: a summer institute in biostatistics (sibs) program, june 17 - july 26, 2024.

THE APPLICATION DEADLINE FOR 2024 HAS PASSED

Completed applications will be reviewed on a rolling basis. 

The Big Data Summer Institute, a SIBS program, is an interdisciplinary training and research program in biostatistics that introduces undergraduate students to the intersection of big data and human health — a rapidly growing field that uses quantitative analysis to help solve scientific problems and improve people’s lives.

Drawing from the expertise and experience of outstanding faculty of several departments at the University of Michigan — biostatistics , statistics , and  electrical engineering and computer science — the institute exposes undergraduate students to diverse experiences and techniques that distinguishes it from any other undergraduate summer program in biostatistics in the country.

This Summer Institute in Biostatistics (SIBS) program is sponsored by the National Heart, Lung, and Blood Institute (NHLBI) , grant R25HL147207, with the intent to introduce undergrad students to the field of biostatistics. Courses will include data collected in studies of heart, lung, blood, and sleep disorders. To learn more about our sister programs, please visit the NHLBI SIBS program website .           

The Big Data Summer Institute, a SIBS program, is hosted by the University of Michigan School of Public Health . All coursework takes place at the school, on the University of Michigan campus in Ann Arbor, Michigan.

Did you miss the BDSI and SIBDS@Columbia joint informational webinar? Click here to watch, and view the presentation here !

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