66 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
-
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
-
will contribute to developing and evaluating state-of-the-art methods for predicting mental health outcomes from multi-modal clinical and digital health data. This position offers the opportunity to work
-
progression and therapeutic response. You will be responsible for all aspects of the research: design of experiments, execution, analysis and reporting of data with guidance and mentoring from me at all stages
-
F. Korstian Distinguished Professor of Forest Economics and Management in Duke’s Nicholas School of the Environment, is hiring a full-time postdoctoral associate to collaborate with him on research
-
Program, and the field site in Kenya, and engage with investigators at all sites across various disciplines. The project will focus on conceptualizing, innovating, and implementing data-driven approaches
-
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