Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- Virginia Tech
- KINGS COLLEGE LONDON
- Nature Careers
- MOHAMMED VI POLYTECHNIC UNIVERSITY
- Durham University
- Technical University of Munich
- UNIVERSITY OF VIENNA
- CNRS
- KTH Royal Institute of Technology
- Max Planck Institute (MPI) for Psycholinguistics
- Argonne
- Barcelona Supercomputing Center (BSC)
- McGill University
- NEW YORK UNIVERSITY ABU DHABI
- Nantes Université
- SUNY University at Buffalo
- Stanford University
- University of Washington
- Aalborg University
- Brookhaven Lab
- ETH Zürich
- Eindhoven University of Technology (TU/e)
- Eindhoven University of Technology (TU/e); 27 Sep ’25 published
- FAPESP - São Paulo Research Foundation
- King's College London;
- LISA UMR7583
- Leibniz
- Princeton University
- Reykjavik University
- Slovak Academy of Sciences
- Technical University of Denmark
- The University of Arizona
- UNIVERSITY OF HELSINKI
- Umeå University
- University of Amsterdam (UvA)
- University of Amsterdam (UvA); today published
- University of Antwerp
- University of British Columbia
- University of Central Florida
- University of Durham
- University of Lodz
- University of Massachusetts
- University of Minnesota
- University of North Carolina at Chapel Hill
- University of Oslo
- University of Oxford
- University of Sydney
- University of Texas at Arlington
- University of Tübingen
- University of Virginia
- University of York;
- Washington University in St. Louis
- 42 more »
- « less
-
Field
-
research in causal representation learning, inference, and discovery; advance explainable models that enable discovery of image-based markers predictive of future disease evolution; and build fair, robust
-
creativity in this endeavour, together with the appropriate skills and knowledge, required to work with Dr. Johnson and collaborators to deliver the research aims. These include (1) imaging altermagnetic
-
off-site manufacturing techniques. - Knowledge of data-driven decision-making approaches for construction optimization. - Hands-on experience with sensor-based communication frameworks, wearable
-
candidate with a strong background in semantic data modeling and knowledge representation, ideally in engineering or scientific domains. You will take the lead in designing, extending, and implementing
-
the estimation of some of the significant water balance components. The candidate is expected to seek an optimal integration between the physical representations of the various processes and the computing power
-
is close. Our cohesive campuses make it easy to meet, work together and exchange knowledge, which promotes a dynamic and open culture. The ongoing societal transformation and large green investments in
-
advanced AI/ML methods for robust analysis and integration. Data sparsity, batch effects, and missing values across different omics layers and platforms. Cross-omics data fusion and representation learning
-
criminal conviction check. About Virginia Tech Dedicated to its motto, Ut Prosim (That I May Serve), Virginia Tech pushes the boundaries of knowledge by taking a hands-on, transdisciplinary approach
-
Metagenomics, meta-transcriptomics and metabolomics data analysis and familiarity with gut microbiome research. Machine learning for genomics (representation learning, generative models, causal inference). Multi
-
outcomes ●casual representation learning for real-world data ● deep learning interpretation, fairness and robustness ●Regularly conduct computational experiments to execute algorithms on various health and