Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Field
-
Research Associate, Arizona Telemedicine Program Posting Number req26712 Department Arizona Telemedicine Program Department Website Link https://medicine.arizona.edu Location Tucson Campus Address Tucson, AZ
-
-learning models (e.g., graph neural networks, equivariant architectures) in collaboration with computer science researchers. Applying developed models to problems in Earth and planetary interiors, such as
-
University. The postdoc will contribute to and help lead projects that may involve concepts and priorities such as knowledge-graph-driven data integration, AI-powered literature review, agentic database search
-
, graph theory, graph-signal processing, and convex/non-convex optimization. Furthermore, our activities are experimentally driven and supported by the COMMLab, the 6GSPACE Lab, the HybridNetLab, the QCILab
-
(R2) Positions PhD Positions Application Deadline 29 Jul 2026 - 23:59 (Europe/Warsaw) Country Poland Type of Contract Temporary Job Status Full-time Hours Per Week 40 Offer Starting Date 1 Oct 2026 Is
-
differential equations, functional analysis, graph theory or similar areas depending on the evolving needs of the department. The successful candidates are also expected to supervise undergraduate and graduate
-
in generating answers in the form of answer maps. You will explore these challenges together with the Principal Investigator as well as a postdoctoral researcher and two PhD candidates. We are looking
-
learning, quantum computing, graph theory, graph-signal processing, and convex/non-convex optimization. Furthermore, our activities are experimentally driven and supported by the COMMLab, the 6GSPACE Lab
-
cloud-based storage and service tools is helpful Preferred Qualifications: MS or PhD in a relevant field Experience with network neuroscience, graph theory, or connectomics Familiarity with high
-
-scale nature, complexity, and heterogeneity of 6G networks, we use tools such as artificial intelligence/machine learning, quantum computing, graph theory, graph-signal processing, and convex/non-convex