73 machine-learning-postdoc-"https:" "Naturalis" Postdoctoral positions at Duke University
Sort by
Refine Your Search
-
ODE/PDE models that include these mechanisms. The postdoc will develop biologically-constrained machine learning–based model discovery pipelines to derive interpretable surrogate ODE/PDE models from
-
information, national origin, race, religion, (including pregnancy and pregnancy related conditions), sexual orientation, or military status. Duke aspires to create a community built on collaboration
-
status. Duke aspires to create a community built on collaboration, innovation, creativity, and belonging. Our collective success depends on the robust exchange of ideas—an exchange that is best when
-
for a postdoc associate. The individual will plan and execute 2-3 active projects per year. These projects are typically collaborative studies between the McIntyre Lab and other Duke faculty, or faculty
-
Duke University, Department of Political Science Position ID: Duke-Department of Political Science-POSTDOC [#31488] Position Title: Position Type: Postdoctoral Position Location: Durham, North
-
• Capacity to manage projects and timelines independently • Comfort giving and receiving feedback in a fast-moving, idea-rich environment Timeline: The postdoc can begin as early as possible, with flexibility
-
Section 5 of the Postdoc Policy for the length of the appointment). The appointment involves substantially full-time research or scholarship and may include teaching responsibilities. The Postdoctoral
-
, United States of America [map ] Subject Area: Chemistry / Polymer Appl Deadline: 2026/02/13 11:59PM ** Position Description: Apply Position Description Postdoc position in polymer informatics. A postdoctoral position is
-
: Engineering / Biomedical Appl Deadline: none (posted 2025/12/10) Position Description: Apply Position Description Postdoctoral Associate The McIntyre Lab is currently hiring for a postdoc associate. The
-
, or engineering. Our research integrates mathematical modeling, machine learning, and quantitative experiments to understand and control the dynamics of microbial communities in time and space. Ongoing projects