Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
- Harvard University
- Hong Kong Polytechnic University
- University of Oslo
- Dana-Farber Cancer Institute (DFCI)
- Indiana University
- King's College London
- Nanyang Technological University
- National University of Singapore
- Center for Drug Evaluation and Research (CDER)
- City of Hope
- Fundació Hospital Universitari Vall d'Hebron- Institut de recerca
- Integreat -Norwegian Centre for Knowledge-driven Machine Learning
- North Carolina A&T State University
- Singapore University of Technology & Design
- Tohoku University
- University of British Columbia
- University of California
- University of Waterloo
- Zintellect
- 10 more »
- « less
-
Field
-
. • Strong background in autonomous robotic systems, unmanned aerial systems (UAS), or multi-agent robotics. • Demonstrated expertise in one or more of the following areas: o Counter
-
schools in the world. For more details, please view https://www.ntu.edu.sg/mae/research . We are looking for a Research Fellow in Multi-Agent Path Planning for Autonomous Drone Operations to develop
-
schools in the world. For more details, please view https://www.ntu.edu.sg/mae/research . We are looking for a Research Fellow in Multi-Agent RL for Autonomous Drone Swarm to develop learning-based
-
at the time of application; (b) strong research experience in one or more of the following areas: LLMs, AI agents / agentic AI, multi-agent systems, AI planning and reasoning, distributed systems, software
-
molecular drivers. Develop AI agents and LLM-based computational workflows for biomedical research, including automated dataset discovery, quality assessment, multi-omics analysis, biological interpretation
-
data challenges. Responsibilities Design and implement LLM-based methods for clinical data harmonization, semantic normalization, and ontology alignment Develop multi-agent or RAG-style (retrieval
-
staff will play a key role in building and integrating of AI agents into gaming scenarios (e.g., gameplay, interactions, procedural content generation, dynamic narratives), and integrating a multimodal
-
, multimodal, and agentic AI, as well as foundation models, with a focus on geometric deep learning, large-scale knowledge graphs, and large language models. Fellows will also have the opportunity to apply
-
). Hands-on experience with game AI agents and/or GUI agents such as Mineflayer, Unity ML-Agents, or similar. Solid expertise in computer vision techniques, transformer architectures, and multi-modal
-
field. Hands-on experience in designing and implementing software systems involving multi-agent frameworks. Familiarity with immersive platform development (e.g., Roblox, Minecraft), including scripting