Sort by
Refine Your Search
-
expertise in metabolism and cardiac physiology with technical skills in metabolic activity measurements, mouse model handling, in vivo physiological measurements, PCR, Western blot analysis, experience
-
. Ideally candidates will have expertise in both quantitative methodologies (e.g., structural equation modeling, multilevel regression, survey development validation, item-response theory, etc.) and
-
and non-myocyte cells; utilizes CRISPR-Cas9 genome editing to model genetic cardiovascular diseases; performs molecular biology techniques (qPCR, Western blotting, cloning, library preparation for omics
-
, manipulating and producing recombinant VSV vaccines, testing vaccination regimens, conducting T-cell proliferation assays, and performing antibody neutralization experiments using various mouse models
-
. Candidates should have a strong research record in LLM-based agents, reinforcement learning, or large language models, preferably in areas closely aligned with the topics outlined above. Desired: We are
-
agricultural landscapes. The goals of the project are to quantify change over time and also identify important processes relevant process-based modeling of dynamic soil properties. The postdoctoral researcher
-
of microvascular endothelial dysfunction in heart failure, sepsis, and related inflammatory conditions. Utilize in vitro and in vivo models, including mouse models of sepsis (e.g., CLP, LPS), ischemia–reperfusion
-
computational modeling; coordinates the development and implementation of new and/or revised research methodologies; prepares research papers and manuscripts for publication and presentation at conferences and
-
methylation, chromatin accessibility), and clinical data. · Develop, apply, and benchmark machine learning and statistical models for subtype discovery, classification, and outcome prediction. · Contribute
-
the supervision of Dr. Joseph Kwon. We’re seeking a creative Postdoctoral Scholar to join our team and advance cutting-edge multiscale and hybrid modeling—integrating first-principles simulations with