85 parallel-computing-numerical-methods-";" Postdoctoral positions at Yale University
Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Field
-
contribute to analyses and processing of data. They will become familiar with high performance computing environments and parallel processing, as well as cloud computing infrastructure. They will
-
dozens of classes of bacterial riboswitches and other structured noncoding RNAs. We are now applying similar genome-scale discovery methods to identify functional RNA regulatory elements in mammals, with
-
, integrating multi-omics data, applying advanced data science approaches, and developing novel statistical methods. Preferred Qualifications Ph.D. in computational biology, bioinformatics, human genetics
-
computational genomics, clinical artificial intelligence, and imaging genetics. This position offers an exciting opportunity to develop novel algorithms and deep learning methods for large-scale genomic
-
Technology Studies. Preferred focus areas: critical computing/artificial intelligence studies; labor and automation technologies; medicine/alternative medicine; chronic illness and/or disability studies
-
(QBio). Our research connects mathematical and statistical foundations with computational methods, drawing on challenges in structural biology to develop ideas with broader applications across data
-
and high-performance or GPU-accelerated computing environments. Applying rigorous methods for external validation, transportability, subgroup performance, fairness, uncertainty quantification, and
-
Koch lab is seeking a postdoctoral scientist with expertise in population genetics and a motivated interest in human genetics. Our lab develops novel methods, theory, and analysis paradigms. We are
-
, machine learning and deep learning methods, and the responsible conduct of research. Training: The candidate will receive training in implementing advanced machine learning and deep learning models, and NLP
-
PWUD. The Postgraduate Associate will assist with development of IRB protocols, survey instruments, mixed methods research, stakeholder engagement, data-collection tools (qualitative and quantitative