-
graphical models, causal inference and machine learning. Dr. Liu's research interests lie in modeling the rapidly-accumulating big data (e.g., muti-omics) in biology and medicine for precision medicine via a
-
about the material behavior and its impact on performance. Using simulation data to train machine learning models of microstructure evolution. Mentoring and directing undergraduate, masters, and PhD
-
, supply chain systems, and transportation systems. We also currently host methodological research in data analytics, machine learning, human systems engineering, optimization, simulation, and stochastic
-
colleagues, researchers, and educators from throughout the University of Florida community to create, identify, and evaluate learning resources and services in the areas of computer vision; works with students
-
Analysis About the Mentor: Dr. Shao obtained his PhD degree in Electrical and Computer Engineering from the University of Iowa in 2019, under the supervision of Dr. Gary E. Christensen (IEEE Fellow, AIMBE
-
. Mingjie Liu, focusing on the development and implementation in advanced machine learning and deep learning models to predict new materials and molecule properties. This one-year appointment is renewable
-
://biostat.ufl.edu/ ) is accepting applications for a fully-funded postdoctoral associate position. This position, available immediately, focuses on developing statistical, machine learning and deep learning methods
-
, and multi-omics data analysis. They also develop novel diagnostic and clinical applications in the field of comparative oncology deploying AI and machine learning. The best-qualified candidate will have
-
with education and experience. Minimum Requirements: PhD in Computer & Information Science & Engineering or a related field. Preferred Qualifications: Special Instructions to Applicants: The search
-
group as well. The group's research interests include axion and dark matter phenomenology, gravitational wave phenomenology, BSM model building, applications of machine learning to particle physics, and