Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- Nanyang Technological University
- National University of Singapore
- SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
- Harvard University
- University of Arkansas
- Hong Kong Polytechnic University
- Indiana University
- Center for Drug Evaluation and Research (CDER)
- University of British Columbia
- University of New South Wales
- University of Texas at Austin
- Aarhus University
- Argonne
- Brunel University London;
- City of Hope
- Durham University
- Integreat -Norwegian Centre for Knowledge-driven Machine Learning
- King's College London
- King's College London;
- Monash University
- NTNU - Norwegian University of Science and Technology
- New York University
- UNIVERSITY OF SOUTHAMPTON
- Universidade de Coimbra
- University of Beira Interior
- University of California
- University of Michigan
- University of Minho
- University of Oslo
- Zintellect
- 20 more »
- « less
-
Field
-
preferred. In addition, the successful candidate should demonstrate these skills: · Expertise in machine learning and AI, particularly LLM fine-tuning and reinforcement learning · Experience with multi-agent
-
timely research question: How can Large Language Models (LLMs) and intelligent agents support transparent, scalable, and auditable clinical data harmonization? We are particularly interested in: LLM-driven
-
Law School - Durham University . Key responsibilities: The successful candidate will contribute to teaching Intellectual Property Law across Durham Law School’s LLB and LLM programmes, with the ability
-
or application. Strong technical expertise in one or more of the following areas: Computer Vision and Image Processing Machine Learning, Deep Learning, and Reinforcement Learning Large Language Models (LLMs) and
-
hybrid approaches combining modelling and simulation (M&S) with AI and other emerging techniques (LLMs) will be highly regarded • A track record of significant involvement with the profession and/or
-
areas: Computer Vision and Image Processing Machine Learning, Deep Learning, and Reinforcement Learning Large Language Models (LLMs) and Multimodal Models Generative AI, Agentic AI, Physical AI, and
-
set by the project is to develop a system capable of integrating up to four types of sources—audio, text, tables, and articles—into an LLM model. We also aim to develop a model that automatically
-
safety and security; (iii) AI for public health. Their research focuses on fundamental research problems in generative AI approaches using LLM agents and diffusion models to scale up AI for social impact
-
; distributionally robust optimization; 2) Graph Neural Networks, Large Language Models (LLMs), and geometric deep learning; and 3) federated learning and privacy preserving computing. Basic Qualifications Candidates
-
programming, including programming skills in R and/or Python. Preferred Qualifications Experience with or willingness to learn using LLMs for psychological research. Experience with or willingness to learn open