72 assistant-professor-and-data-visualization Postdoctoral positions at Duke University
Sort by
Refine Your Search
-
to the seminar’s principal investigators: Professor Charlotte Sussman (charlotte.sussman@duke.edu) and Professor James Mulholland (mulholland@ncsu.edu ). Duke is committed to encouraging and sustaining work and
-
2026/05/31) Position Description: Apply Position Description Postdoctoral Research Associate in Climate Economics and Urban Resilience The lab of Yichun Fan, Assistant Professor of Climate Economics at
-
environments is necessary. Experience with data cleansing, wrangling, visualization, modelling, and interpretation is necessary. Previous experience in data science is highly desired. Previous experience in
-
candidate will work directly with experimental scientists within a wet lab setting to facilitate the management, analysis, and visualization of the mass spectrometry-based proteomic data generated in our
-
and repeat by other lab members. · Update lab members on new developments in commercial reagents and techniques. · Compile and document results, maintain lab notes, and assist in writing reports and
-
, interpret and discuss experimental data with PI. Apply for funding (postdoctoral fellowship opportunities and contribute to larger lab grants). Write and submit manuscripts. Help other lab members
-
Bold. Position Description: Perform a variety of technical duties involved in conducting behavioral medicine research studies; Assist with development of study intervention protocols and materials
-
one other course as desired, (2) work closely with the Professor on his ROCKWOOL-funded research projects on the intergenerational transmission of social marginalization and the intimate partner
-
. The projects seek to improve our scientific understanding of memory function by investigating (a) the nature of mnemonic representations using cutting-edge representational similarity analyses (RSA) of fMRI data
-
for a Postdoctoral Scholar. The Scholar will conduct research on Bayesian spatiotemporal modeling methodology under the direction of Professor David Dunson at Duke on developing novel models motivated by