Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- Harvard University
- SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
- Nanyang Technological University
- National University of Singapore
- University of Arkansas
- University of Michigan
- Institute for Basic Science
- University of British Columbia
- University of Oslo
- Wayne State University
- ;
- Florida Atlantic University
- Francis Crick Institute
- Hong Kong Polytechnic University
- INESC TEC
- Integreat -Norwegian Centre for Knowledge-driven Machine Learning
- Marquette University
- Max Planck Institute of Biochemistry, Martinsried
- Middlesex University
- Middlesex University;
- NTNU - Norwegian University of Science and Technology
- Northeastern University
- Tampere University
- University of Bergen
- University of Texas at Austin
- University of Waterloo
- Visterra, Inc.
- 17 more »
- « less
-
Field
-
Apply Now How to Apply Applications should be sent to [email protected] and [email protected] with the subject line: Postdoctoral Application - Granular materials using graph theory. Interested
-
(m/f/d) in Graph Learning. Project overview This position offers a rare opportunity to contribute to the future of machine learning for graph-structured data. While machine learning has transformed
-
To support the UrbanHeatMap project, which aims to develop scalable, high-resolution ambient temperature mapping methods by integrating outdoor microclimate measurements, mobile sensing data, satellite-derived land surface temperature, and urban morphology information. The Research Assistant...
-
air temperature maps • Develop and train Graph Neural Network (GNN) and Long Short-Term Memory (LSTM) architectures to model complex spatial and temporal dependencies in urban microclimate data
-
foundation models, knowledge graph/ontology, federated learning or collaborative agents, AI security, etc.; (c) have experience in research proposal development; (d) have strong publication records in
-
://dimag.ibs.re.kr/ Successful candidates for the research fellowship positions will be new or recent PhDs with outstanding research potential in all fields of Discrete Mathematics with emphasis on Structural Graph
-
plus · Experience with one or more of representation learning, generative modeling, graph neural networks, transformers, or foundation model pretraining and fine-tuning is a plus
-
, 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
-
, 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
-
Architecture: Architect, build, and evaluate multi-agent systems powered by LLMs and machine learning, incorporating Orchestrator and Memory agents, vector databases, and knowledge graphs to enable complex goal