Albert Jin
About Albert Jin
Albert Jin is a biophysicist at the National Institutes of Health, specializing in nanotechnology and nanomedicine. He has extensive experience in advanced techniques such as Atomic Force Microscopy and Optical Nanoscopy, and has contributed to research on various topics including malaria vaccine proteins and membrane fusion.
Work at National Institutes of Health
Albert Jin has been a Biophysicist at the National Institutes of Health (NIH) since 1992. He works at the NIH in Bethesda, MD, where he serves as the Chief of the Nanoinstrumentation and Force Spectroscopy Section within the Laboratory of Cellular Imaging and Macromolecular Biophysics. His role involves leading research initiatives and overseeing projects that focus on advanced biophysical techniques.
Education and Expertise
Albert Jin holds a Master of Science degree from Penn State University, where he studied from 1985 to 1988. He also earned a Ph.D. from the University of Maryland, completing his studies from 1988 to 1992. Additionally, he pursued post-graduate studies at the NIH FAES. His educational background supports his specialization in advanced techniques such as Atomic Force Microscopy and Optical Nanoscopy, as well as Single Molecule Force Spectroscopy and Instrumentation Development.
Background
Albert Jin completed his Bachelor of Arts degree at Nanjing University from 1981 to 1985. His academic journey laid the foundation for his extensive career in biophysics and nanotechnology. His research interests encompass Nanotechnology and Nanomedicine, with a focus on the development of innovative instrumentation and techniques for studying biological systems.
Research Focus and Projects
Albert Jin engages in research related to various aspects of biophysics, including Lipid Bilayers, Liposomes, and Carbon Nanotubes. His work also includes significant contributions to the study of Malaria Vaccine Proteins and Membrane Fusion. He actively participates in projects that leverage his expertise in Bioinformatics and Biomedical Modeling to advance understanding in these fields.