Sort by
Refine Your Search
-
image analysis, machine learning or deep learning, python and/or MATLAB, scientific computing and numerical methods. Experience with computing, PyTorch, spectral CT, photon-counting detectors, or
-
analyses of micro-randomized trials and experimental designs for Markov decision processes. The candidate is expected to innovate statistical methods and algorithms, create software implementations
-
, and development of tools suitable for high-performance computing environments. Experience with parallel computing and workload management systems such as SLURM is highly desirable. Model Calibration
-
of computational biology, machine learning, and tissue biology. In this role, you will work closely with Dr. Yi Zhang and collaborators to develop and apply computational methods for analyzing
-
biomedical discovery. You will help design and implement machine learning models, maintain computational pipelines, and analyze complex biological datasets using high-performance computing environments. This
-
science methods into starting and ongoing projects Assist CHeRI PIs with implementation science resources and deliverables. Learn background/research methods of studies for which analysis is
-
groundbreaking methods to objectively measure dietary intake using DNA sequencing. Our research spans North Carolina and global communities, generating insights into nutrition, disease risk, and the
-
: Functional genomics and pooled screening technologies CRISPR knockout, CRISPRa/i, or base-editing platforms NGS library preparation and sequencing methods, including: ATAC-seq CUT&RUN CUT&Tag RNA-seq Hi
-
, artificial intelligence, and data-driven discovery. Learn more about the iMIND Study Team: https://dukeeyecenter.duke.edu/imind Be Bold. Join a multidisciplinary research team at the forefront of
-
study implementation and routine problem resolution. Knowledge, Skills and Abilities Can easily use computing software and web-based applications (e.g., Microsoft Office products and internet browsers