Sort by
Refine Your Search
-
Listed
-
Country
-
Employer
- Cornell University
- NEW YORK UNIVERSITY ABU DHABI
- AALTO UNIVERSITY
- Nature Careers
- Princeton University
- University of North Carolina at Chapel Hill
- AI4I
- Aarhus University
- Brookhaven National Laboratory
- Delft University of Technology (TU Delft); today published
- Duke University
- Ecole Normale Supérieure
- Inria, the French national research institute for the digital sciences
- Instituto Politécnico de Bragança
- Jerzy Haber Institute of Catalysis and Surface Chemistry, Polish Academy of Sciences
- Linköpings universitet
- Luleå University of Technology
- North Carolina A&T State University
- Rutgers University
- THE UNIVERSITY OF HONG KONG
- Tampere University
- University of California Riverside
- University of Galway
- University of Luxembourg
- University of Minho
- University of Southern Denmark
- University of Twente (UT)
- University of Washington
- Université de Bordeaux / University of Bordeaux
- Virginia Tech
- Örebro University
- 21 more »
- « less
-
Field
-
candidate will join an interdisciplinary team working to combat multi-resistant Gram-negative infections (CREs and 3GCs) through innovative chemical strategies. The postdoctoral project is part of our current
-
agents. The successful candidate will join an interdisciplinary team working to combat multi-resistant Gram-negative infections (CREs and 3GCs) through innovative chemical strategies. The postdoctoral
-
implications: explore scenarios of AI’s commercial development, particularly the rise of agentic and multi-agent systems, and assess their potential environmental impacts. Indirect effects: estimate the indirect
-
physical environments. This position focuses on research at the intersection of computer graphics, generative AI, and robotics, encompassing topics such as generative modeling, reinforcement learning, multi
-
bottleneck. You will explore methods to partially automate context engineering, enabling faster development cycles, stronger scalability, and more autonomous, high-fidelity multi-agent systems within
-
workflow optimization • Network, graph, and agent-based modeling for care delivery • Health equity, patient access, and system resilience • Multi-modal data integration using EHR, claims, environmental, and
-
, multi-agent systems, and agent based modelling) and energy systems (energy modelling, renewable energy, energy management, and energy in agriculture). The position will be under the direction of Dr. Karl
-
the next generation of secure agentic AI systems through cutting-edge research in adversarial machine learning and formal verification. The Role As a research scientist, you will contribute to frontier AI
-
, and agent-based modeling for care delivery Health equity, patient access, and system resilience Multi-modal data integration using EHR, claims, environmental, and behavioral datasets The successful
-
adaptation of existing approaches for scientific applications; (ii) Large Language Models (LLMs) and multi-modal foundation Models (iii) Agentic AI techniques for scientific domains; and (iv) techniques