Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- Nanyang Technological University
- University of Oslo
- Zintellect
- Harvard University
- National University of Singapore
- SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
- University of Stavanger
- AUSTRALIAN NATIONAL UNIVERSITY (ANU)
- INESC TEC
- UiT The Arctic University of Norway
- University of Bergen
- University of South-Eastern Norway
- Carnegie Mellon University
- Center for Drug Evaluation and Research (CDER)
- Cornell University
- DAAD
- Dana-Farber Cancer Institute (DFCI)
- Macquarie University
- Max-Planck-Institut für Bildungsforschung
- Mayo Clinic
- Queen's University Belfast
- Ryerson University
- Tampere University
- The Francis Crick Institute;
- University of Agder
- University of British Columbia
- University of California
- University of Maryland, Baltimore
- University of New South Wales
- University of Nottingham
- University of Texas at Austin
- 21 more »
- « less
-
Field
-
for Science with inadequate attention and support. This proposal addresses the gap by focusing on the development of optimized implementations for AI for Science workloads. Bespoke communication and computation
-
key role in driving high-impact research, developing innovative objectives, and formulating proposals within cutting-edge fields, including Computer Vision, Digital Healthcare, AI Optimization, and
-
? As an Oak Ridge Institute for Science and Education (ORISE) participant, you will join a community of scientists and researchers studying adversarial interactions, multi-agent systems, and decision
-
, cavity/waveguide networks, and polaritonic circuit elements. Design, fabricate, assemble, optimize and experimentally characterize integrated polaritonic devices and waveguides. Develop and operate optical
-
develop and optimize scientific and engineering applications leveraging high-speed network capability provided by the Energy Sciences Network or run on next-generation high performance computing and data
-
modeling. Integrate and evaluate automatic segmentation algorithms within a reproducible anatomical-modeling workflow. Refine segmented geometries and optimize surface and volumetric mesh generation
-
Fracture Network (DFN) and Embedded Discrete Fracture Modeling (EDFM) Tracer design and interpretation Machine learning or optimization for reservoir management Experience working with field-scale geothermal
-
language processing or text analytics, network analysis, optimization, or social media research. Proficiency in Python is required; experience with R, large language models, survey design or experimental research, and
-
photovoltaic generation, hydrogen production, and storage alternatives with microgrid-driven power distribution. Through advanced modelling and optimization techniques, this research aims to identify optimum
-
well as communicate with research networks within the scientific community. Learning Objectives: As part of this learning experience, you may: Learn how grapevine populations and germplasm are evaluated to identify