Graduate Funding
The following training grants are related to biomathematics and computational medicine.
For a complete list of pre-doctoral and post-doctoral training grants in the biomedical and life sciences at UCLA, see the webpage UCLA's Competitive Research Training Grant Programs
Data Science for Precision Health NLM T15 Training
►Biomedical Data Science Training Program for Precision Health Equity
Genomic Analysis Training Program (GATP)
The Genomic Analysis Training Program is funded by an NIH grant and supports UCLA pre-doctoral students whose goal is to conduct research in genomics. The program provides its trainees with stipends and funding for academic fees, travel, and research. For more information, contact Lorraine Hartman.
Pre-doctoral and Post-doctoral Training Program in Neurobehavioral Genetics
The Center for Neurobehavioral Genetics is accepting nominations of candidates for the NIH-funded predoctoral and postdoctoral training program in neurobehavioral genetics. For more information, please contact Yoon Jung.
Past Funding Opportunities
Systems and Integrative Biology (SIB) training grant
The NIH-sponsored Systems and Integrative Biology training grant supports pre-doctoral students who seek a balanced and rigorous training in mathematics and biology/biomedicine with a special emphasis on research in mathematical modeling in biology or biomedicine. Trainees will complete a minimum of 20 quarter units of advanced courses in quantitative methods, 20 quarter units in biological sciences, one course on ethics in biological/medical research, and at least one quarter per year of directed research in the laboratory of a participating faculty member. For more information, please contact the director, Tom Chou, or the student affairs officer, Samantha Andrews.
►SIB Program Summary
►SIB Training Requirements
ModEling and uNdersTanding human behaviOR (MENTOR) NRT
The NSF-funded MENTOR program offers unique opportunities to train future scientists to develop and deploy new mathematical models, analytical methods, and application tools that directly address the challenges in managing, analyzing and integrating new and diverse types of data and knowledge across scientific and engineering disciplines. It draws upon a core group of interdisciplinary faculty researchers and teachers across UCLA. For more information, contact Andrea Bertozzi (PI) or Wei Wang (co-investigator).