31 parallel-programming "Intelligent Systems Group" Postdoctoral positions at Duke University
Sort by
Refine Your Search
-
Listed
-
Category
-
Field
-
closely related quantitative field Demonstrate strong computational and statistical training, including experience with complex data analysis Have proficiency in statistical programming (e.g., R, SAS
-
the mechanisms of, and interventions for, influenza virus disease using high-throughput genomic screening approaches, primary cell culture systems, and animal models of influenza disease. For more
-
informatics, biostatistics or a related discipline. Required qualifications include (1) expertise and experience in machine learning, (2) proficiency in computer programming, (3) good verbal and written
-
and verbal communication skills. Strong programming skills in R. Proficiency working within UNIX/Linux environments. Preferred Qualifications Experience with Bayesian statistical methods. Experience
-
sequencing Spatial transcriptomics Multiplex imaging Bioinformatics R or Python programming Tissue culture techniques Animal models Interest in translational cancer research, immunotherapy, and neuro
-
, machine learning, or biomedical data science. Strong programming and software development skills. Experience working with complex biomedical, imaging, or clinical research datasets. Excellent scientific
-
translational research group within Duke Anesthesiology focused on microbiome–immune interactions in critically ill and perioperative patients. Our research combines prospective ICU cohort studies; advanced
-
while gaining experience with cutting-edge technologies, including genetically engineered mouse models, patient-derived models, single-cell and spatial genomics, organoid systems, and preclinical
-
interest in metastasis and the tumor microenvironment. Our group has a diverse and stimulating environment with projects in basic and translational research as well as clinical trial studies
-
advancing next-generation medical imaging technologies. Your expertise in software development, machine learning, and imaging systems will help drive groundbreaking discoveries that improve