Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Field
-
/UKCA), and standards for medical/assistive devices. Drug delivery systems – nanoelectronics, nanoparticles, and similar for therapeutic agent release (including closed loop/triggered release
-
to join our team. In this role, you will design, develop, and deploy state-of-the-art generative AI models, directly impacting our platform's ability to provide interactive and intelligent tools for our
-
planning tool which models how autonomous agents make decisions in an uncertain world. This project focuses on designing systems of interaction between agents in order to achieve complex, multi-objective
-
model, competency models, and simulation standards of practice. Educates staff on policies and procedures, supporting practice changes based on evidence-based guidelines. Leadership Contributes
-
are based on cutting-edge research carried out within 6 joint research units: GEPEA, IRISA, LATIM, LABSTICC, LS2N and SUBATECH. The proposed thesis is part of the research activities of the team OSE
-
Postdoc position in modeling and analysis of cyber-physical systems At the Technical Faculty of IT and Design, Department of Computer Science, a full-time postdoc position in modeling and analysis
-
) integrate crop, hydrologic, and GHG/energy models to quantify trade-offs among yield, water, emissions, biodiversity, etc., (3) create decision-support tools and maps to guide farmers, extension agents, and
-
pathogenesis and their potential as therapeutic agents and diagnostic tools. Using in vitro, ex vivo, and in vivo models, the lab studies EVs derived from amniotic fluid stem cells (AFSCs) and other perinatal
-
community. We are committed to excellence, providing unparalleled expertise, and maintaining a world-class standard in service. Please visit us at: https://fs.ucf.edu/ or Facebook and Instagram: UCF
-
modeling and coordination of interdependent infrastructure systems and their subsystems (such as networks of transportation, gas, electricity grid), multi-agent reinforcement learning for distributed