Sort by
Refine Your Search
-
Listed
-
Employer
- Cornell University
- Duke University
- Argonne
- Harvard University
- Northeastern University
- Oak Ridge National Laboratory
- Texas A&M AgriLife
- Texas A&M University
- Boston University
- Carnegie Mellon University
- Iowa State University
- New York University
- Princeton University
- Research Center for Molecular Medicine (CeMM), ÖAW
- St Jude Children's Research Hospital
- Stanford University
- The University of South Dakota
- University of California
- University of California Irvine
- University of North Carolina at Chapel Hill
- University of Pittsburgh, Pittsburgh , Pennsylvania, US
- University of Utah
- University of Washington
- 13 more »
- « less
-
Field
-
formation energies, adsorption energies, metal-support interactions) and correlate them against measured kinetic parameters. Contribute to multi-agent hypothesis generation and validation architectures and to
-
research teams: 1) The AI Group: Experts in systems, control, optimization, Large Language Model (LLM) training, domain adaptation, and instruction tuning, agentic AI orchestration, and reinforcement
-
new NIH-funded Center for Excellence in Multiscale Immune Systems Modeling . This position focuses on the development, calibration, and analysis of multiscale agent-based models (ABMs) and differential
-
candidate will conduct cutting-edge research on coordinated autonomous ground and aerial robotic systems, focusing on multi-agent collaboration, autonomous decision-making, perception, planning, and control
-
simulations in fusion devices. Support coordinated multi-physics simulations of fission reactor core, fusion device blankets, and other system components. Develop reduced-order calibration approaches and apply
-
for large language models and agentic AI systems. Experience designing and developing multi-agent systems, tool-using AI agents, retrieval-augmented generation systems, or autonomous reasoning and planning
-
the mechanisms of, and interventions for, immuno-senescence and aging in lung transplantation using high-throughput multi-‘omic approaches, primary cell culture systems, and animal models of transplantation. Ph.D
-
experiment with multi-agent reinforcement learning workflows that coordinate component choices and parameters while enforcing system-level feasibility. LLM-assisted engineering workflows: contribute to domain
-
motivated Postdoctoral Research Fellow to develop and apply innovative, data-driven models for seismology, with a focus on developing cutting-edge foundation models. This is an exceptional opportunity
-
/Python), deployment (to the agents' onboard computational hardware using the Robot Operating System), and experimental testing (on unmanned vehicle swarms). A solid competency with the standard