Sort by
Refine Your Search
-
, there are several exciting opportunities for a variety of very interesting projects beyond structure-function studies of cytoskeletal proteins that control signaling downstream of adherens junctions and focal
-
collaboration with the UF Artificial Intelligence initiative. The successful candidate will have the opportunity to work on cutting-edge projects aimed at building large-scale models for neuroimaging and
-
Development (50%): Develop and apply advanced statistical modeling and coding skills (primarily in R) to build a QMRA framework using data from both the scientific literature and those collected from
-
unravel the complex relationships between land use changes and fire regimes over the past 60 years. The successful candidate will lead efforts to: Develop advanced deep learning algorithms for classifying
-
postdoctoral associate positions, starting immediately. Dr. Liu has extensive experience in big data analytics, systems biology, probabilistic graphical models, causal inference and machine learning. Dr. Liu's
-
on conducting problem-oriented and policy-relevant research, developing econometric models to understand the economic and behavioral incentives for using new farm management practices and technology adoption and
-
animal models and extending these insights to understanding and intervening in human diseases. Successful candidates will be self-motivated scientists, with a passion for advancing cutting-edge research
-
protostellar evolution models to radiative transfer grids. The goal is to synthesize these protostar models into protocluster models and compare them to JWST and ALMA data. The applicant must have a Ph.D. in
-
to contribute to research in concentrating solar thermal (CST) and solar fuels. Key Responsibilities: • Conduct research in CST and solar fuels, focusing on thermochemical reaction modeling and experimentation
-
fibroids and eliminating fibroid health disparities. The project will provide education on fibroid symptoms/management, identify barriers to care, and improve risk prediction models to identify women with