Sort by
Refine Your Search
-
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
-
new NIH-funded Center for Excellence in Multiscale Immune Systems Modeling. This position focuses on leveraging and developing new equation learning methods, such as Physics-Informed Neural Networks
-
, with a particular emphasis on Urban Resilience to Climate Risks. Current research themes include: • Adaptation of People: Leveraging big data and computational methods to analyze adaptation behaviors and
-
Systems Modeling. This position focuses on leveraging and developing new equation learning methods, such as Physics-Informed Neural Networks (PINNs), Biologically Informed Neural Networks (BINNs), and
-
policies pertaining to other schools at Duke University. The postdoc candidate is expected to: 1) Develop novel methods for incorporating scientific machine learning in solving problems in solid mechanics
-
quantitative methods and excited about discovering physical principles of biological organization. Minimum Requirements: PhD in a scientific disciplines, ideally Biology, Bioengineering, Physics or Math
-
design and management; mentorship and coordination skills; familiarity with plant ecophysiology lab methods. Position details: • Start date: Flexible, as early as August 2026 • Location: Durham, North
-
learning, or related quantitative methods preferred but not required. Be Bold. Position Description: Engage in substantially full-time research or scholarship under the guidance of a faculty mentor, focusing
-
animal species, generating standardized data that works effectively across diverse languages and cultural contexts while eliminating traditional barriers of recall bias. These methods are being deployed in
-
evaluation methods, discrete choice experiments, systematic reviews, and meta-analysis, with high levels of proficiency in associated software (e.g., Stata, R, Ngene). Applicants should have knowledge