Sort by
Refine Your Search
-
Listed
-
Country
-
Employer
- Harvard University
- AbbVie
- Nanyang Technological University
- The University of Alabama
- University of British Columbia
- Wayne State University
- Auburn University
- Australian National University
- FCiências.ID
- Genentech
- KINGS COLLEGE LONDON
- King's College London
- Korea Institute for Advanced Study
- LINGNAN UNIVERSITY
- Marquette University
- Monash University
- NTNU - Norwegian University of Science and Technology
- Nature Careers
- Northeastern University
- RMIT UNIVERSITY
- RMIT University
- UNIVERSITY OF ADELAIDE
- University of Adelaide
- University of Alabama, Tuscaloosa
- University of Houston Central Campus
- University of Liverpool
- University of Oslo
- University of Oxford
- University of San Francisco
- University of Texas at Austin
- University of Waterloo
- 21 more »
- « less
-
Field
-
. Investigate and build robust data and AI agent pipelines for continuous learning and knowledge acquisition, including annotation strategies and knowledge graph development for aquaculture stress events. Design
-
: Developing and deploying machine learning models (e.g. graph neural networks, neural force fields, diffusion models) for molecular property prediction and molecular generation. Integrating quantum chemistry
-
, consolidating metadata and other various sets of data to prepare databases for cross-disciplinary AI research and learning. Incorporates open knowledge graph networks. Takes the lead in drafting scientific papers
-
degree in mathematics, strongly encouraged to apply. Experience and demonstratable knowledge in deep learning and one or more of the following: transformer networks, implicit neural functions, graph neural
-
learning and one or more of the following: transformer networks, implicit neural functions, graph neural networks and/or probabilistic graphical models; and causal inference. • An outstanding publication
-
. Research areas include Representation Learning, Machine learning and Optimization on graphs and manifolds, as well as applications of geometric methods in the Sciences. This is a one-year position with
-
as required. Demonstrated high level of written and oral communication skills. Preferable Experience in eukaryotic cell culture/tissue culture Expertise with advanced graphing and/or data analysis
-
workflows — including methods for knowledge graph construction, advanced querying, and data quality assurance. Contribute to aligning the developed methods with emerging standards for information modelling
-
regarding research results. Preferred Qualifications: Experience with deep/graph neural networks and active involvement in data science and machine learning projects. Experience in multimodal data fusion (e.g
-
available for two years. Keywords: Geometric Deep Learning, in particular Graph Neural Networks, Deep Reinforcement Learning, Generative Modelling, in particular Denoising Diffusions, Combinatorial