Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- Argonne
- Aarhus University
- MOHAMMED VI POLYTECHNIC UNIVERSITY
- NEW YORK UNIVERSITY ABU DHABI
- Stanford University
- King's College London
- Pennsylvania State University
- University of Florida
- Baylor College of Medicine
- Blekinge Institute of Technology
- Delft University of Technology (TU Delft)
- Eindhoven University of Technology (TU/e)
- FAPESP - São Paulo Research Foundation
- Oak Ridge National Laboratory
- Queen Mary University of London
- UNIVERSITY OF VIENNA
- University of Amsterdam (UvA)
- University of Basel
- University of Copenhagen
- University of Oxford
- Yale University
- ;
- Aston University
- Boston University
- Carnegie Mellon University
- Cornell University
- ETH Zürich
- Ecole Polytechnique Federale de Lausanne
- Harvard University
- Helmholtz-Zentrum Geesthacht
- Inria, the French national research institute for the digital sciences
- KTH Royal Institute of Technology
- Leuphana University Lueneburg
- McGill University
- New York University
- Northeastern University
- Saarland University
- Sandia National Laboratories
- St Jude Children's Research Hospital
- Technical University of Munich
- Texas A&M University
- The University of Iowa
- Toyota Technological Institute
- University College Dublin
- University of California
- University of California Irvine
- University of Canterbury
- University of Central Florida
- University of Connecticut
- University of Lund
- University of Miami
- University of Nebraska Medical Center
- University of North Carolina at Chapel Hill
- University of Oxford;
- University of Turku
- University of Twente (UT)
- Utrecht University
- VIB
- Vrije Universiteit Amsterdam (VU)
- 49 more »
- « less
-
Field
-
. Desirable criteria Experience with training or fine-tuning LLMs or other generative AI models Excellent programming skills and familiarity with modern AI frameworks Downloading a copy of our Job Description
-
platform for X-ray absorption spectroscopy by integrating LLMs, scientific machine learning, physics-aware workflows, and strong computational chemistry/electronic-structure expertise. The researcher will
-
pollution exposure data. Familiarity with LLMs. Special Instructions Please submit the following materials: ● Cover letter describing your research interests, relevant experience, and fit for this position
-
: Leveraging LLM / VLMs for interdisciplinary problems, such as: AI-driven scientific discovery, automating hypothesis generation in finance / natural sciences / physical sciences, enhancing collaborative
-
at the intersection of learning sciences and artificial intelligence, with particular focus on large language models (LLMs), generative AI (GenAI), and assistive AI as tools and partners in learning, identity
-
physiological signals. Experience integrating multiple modalities to build robust AI systems is an advantage. ● Interdisciplinary Applications: Leveraging LLM / VLMs for interdisciplinary problems, such as: AI
-
area of research and development (R&D) of next-generation Edge-AI and Embodied-AI Systems with tiny-LLMs, tiny-VLMs, tiny-VLAs; Agentic-AI systems; and Robust Generative AI targeting hallucination
-
will combine modern AI/LLM-based code generation with formal methods to produce software that is both fast to create and provably trustworthy. The position is part of SAFIR (Secure AI for Intelligent
-
information science, broadly defined. Experience in topological materials/ topological quantum computation/ quantum geometry/ exposure to tensor network methods or and/or AI/LLM for physics would be a positive addition
-
networks, RNNs, LLMs) or in the deployment of such algorithms. Experience with specialized computational architectures such as GPUs, FPGAs, neuromorphic processors, or machine learning accelerators