67 algorithm-development "Grenoble INP UGA" Postdoctoral positions at Yale University
Sort by
Refine Your Search
-
Title of the Position: Postdoctoral Associate Functional Genomics / Regulatory Genomics / Human Evolution & Disease Department and School: Department of Genetics, Yale School of Medicine Anticipated
-
Postdoctoral Associate Position — Functional Genomics / Regulatory Genomics / Human Evolution & Disease (Reilly Lab) Yale University: School of Medicine: Genetics Location New Haven, CT Open Date
-
-driven research group working at the intersection of computational genomics, clinical artificial intelligence, and imaging genetics. This position offers an exciting opportunity to develop novel algorithms
-
was created to advance research in the mathematical, algorithmic, and statistical foundations of data science and their application to other disciplines. In addition to providing support to core foundational
-
on developing biofluid biomarkers that improve diagnosis, define disease heterogeneity, and can be implicated in clinical trials. A major complementary effort in the lab focuses on advanced
-
Astronomy. The institute was created to advance research in the mathematical, algorithmic, and statistical foundations of data science and their application to other disciplines. In addition to providing
-
. The Associate will have the opportunity to engage with not only activities at the Economics department, but also at the Cowles Foundation and the Center for Algorithms, Data, and Market Design (CADMY). Applicants
-
in preclinical neuroimaging, MRI physics, neuroscience, computational data analysis, and multimodal biomarker development. The Yale Small Animal MRI Core provides access to high-field MRI (9.4T and
-
evolution of drug resistance in breast cancer with a specific interest in topoisomerase-1 inhibitor antibody-drug conjugates (TOP1i-ADCs). As a member of the Genomics, Genetics and Epigenetics research
-
neurodevelopmental disorders. The successful candidate will develop and apply experimental and computational approaches to understand gene regulation and disease mechanisms in neural development and to evaluate