Sort by
Refine Your Search
-
. The Postdoctoral Associate will apply his/her technical skills toward development and implementation of machine learning, computer vision, and other algorithms for analysis of medical images and prognostication as
-
Duke University, Computer Science Position ID: Duke -CS -PDA_RUDIN25 [#30110] Position Title: Position Location: Durham, North Carolina 27708, United States of America [map ] Subject Area: Computer
-
Duke University, Nicholas School of the Environment - Durham Program ID: Duke -NSOE-Durham -POSTDOC_MEYER [#28186] Program Title: Postdoctoral Associate - Integrated Toxicology & Environmental
-
. The Ur-BIOME Research Program at Duke University, led by Dr. Nazema Siddiqui in the Department of Obstetrics and Gynecology’s Division of Urogynecology, is seeking a highly motivated Postdoctoral Fellow
-
Gastroenterology Research Training Program Postdoctoral Fellowship The Duke Division of Gastroenterology is seeking applicants for a two-year post-doctoral fellowship within the Duke Gastroenterology Research
-
methods like umbrella sampling, force integration, free energy perturbation, or lambda integration to compute the conformational behavior of individual structures and the thermodynamic stability of assembly
-
research training program, unless research training under the supervision of a senior mentor is a primary purpose of the appointment. · The appointee works under the supervision of a scholar or a department
-
Assessment Models (IAMs) such as GCAM or PAGE. The candidate must have a PhD degree in a related field, be fluent in computer programming, preferably python, and will ideally have experience in working with
-
The appointment is not part of a clinical training program, unless research training under the supervision of a senior mentor is the primary purpose of the appointment The Postdoctoral Appointee functions under
-
independent research activities under the guidance of a faculty mentor in preparation for a full time academic or research career. Conduct research on computational modeling of cortical neuron activation by