Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- Nature Careers
- Technical University of Munich
- Stanford University
- University of Oxford
- MOHAMMED VI POLYTECHNIC UNIVERSITY
- Argonne
- NEW YORK UNIVERSITY ABU DHABI
- University of North Carolina at Chapel Hill
- ;
- Duke University
- New York University
- Pennsylvania State University
- Singapore Institute of Technology
- Technical University of Denmark
- University of Miami
- University of Minnesota
- University of Washington
- Yale University
- Brookhaven Lab
- Leibniz
- University of California Berkeley
- University of Central Florida
- Aarhus University
- Carnegie Mellon University
- Cornell University
- Forschungszentrum Jülich
- Heriot Watt University
- KINGS COLLEGE LONDON
- Northeastern University
- Radboud University
- The University of Arizona
- U.S. Department of Energy (DOE)
- University of California
- University of Florida
- University of Minnesota Twin Cities
- University of Texas at Arlington
- AALTO UNIVERSITY
- Aalborg University
- Chalmers University of Technology
- Cold Spring Harbor Laboratory
- King Abdullah University of Science and Technology
- National Aeronautics and Space Administration (NASA)
- National University of Singapore
- Oak Ridge National Laboratory
- Princeton University
- RIKEN
- Rutgers University
- South Dakota Mines
- Stony Brook University
- Texas A&M University
- UNIVERSITY OF HELSINKI
- UNIVERSITY OF VIENNA
- University of British Columbia
- University of California Irvine
- University of California, Merced
- University of Houston Central Campus
- University of Lund
- University of Maryland, Baltimore
- University of Nevada Las Vegas
- University of Nevada, Reno
- University of North Texas at Dallas
- University of Oklahoma
- University of Vienna
- Virginia Tech
- Wayne State University
- ; Technical University of Denmark
- ; University of Oxford
- ; Xi'an Jiaotong - Liverpool University
- Academia Sinica
- CEA-Saclay
- California State University, Northridge
- Canadian Association for Neuroscience
- Case Western Reserve University
- Centre for Genomic Regulation
- Copenhagen Business School , CBS
- Durham University
- ETH Zurich
- Emory University
- Empa
- Escola Superior de Agricultura Luiz de Queiroz/ESALQ/USP
- European Space Agency
- Genentech
- Ghent University
- Imperial College London
- Indiana university Indianapolis
- Institut Pasteur
- King's College London
- Lawrence Berkeley National Laboratory
- Los Alamos National Laboratory
- Manchester Metropolitan University
- Purdue University
- SUNY University at Buffalo
- SciLifeLab
- Sun Yat-Sen University
- Swedish University of Agricultural Sciences
- Syracuse University
- Texas A&m Engineering
- The Ohio State University
- The University of Chicago
- The University of Iowa
- 90 more »
- « less
-
Field
-
-based sensor data to enhance the prediction of peatland soil properties and functions. You will focus on leveraging machine learning/deep learning techniques along with explainable artificial intelligence
-
Title: Postdoctoral Research Associate - Machine Learning & Advanced Manufacturing Employee Classification: Postdoctoral Research Assoc Campus: University of North Texas Division: UNT-Provost
-
knowledge of methodologies such as deep and statistical learning. Informal enquiries may be addressed to Prof. Andrea Vedaldi (email:andrea.vedaldi@eng.ox.ac.uk) For more information about working at
-
, deep learning, and data analytics will be beneficial. 4. Experience in Dynamo programming would be preferred. Willing to learn and responsible. 5. The appointed candidates will support the planning
-
-based sensor data to enhance the prediction of peatland soil properties and functions. You will focus on leveraging machine learning/deep learning techniques along with explainable artificial intelligence
-
molecular dynamics and path integral simulation methods, machine learning techniques, and electronic structure techniques. Additional background in statistical mechanics and deep eutectic solvents is highly
-
from real world longitudinal data on management and health outcomes for children with mental health conditions. Methods have included deep learning, large language models (LLM), generative AI models (Gen
-
imaging pipelines, and use deep learning to gain insight into biological processes. You will also gain direct exposure to cardiovascular physiology and rodent imaging in close collaboration with biologists
-
activities. Qualifications: Ph.D. in Bioinformatics, Computational Biology, Computer Science, Genomics, or a related field. Strong background in machine learning, particularly deep learning and natural
-
Qualifications: Experience with aging populations or neurodegenerative diseases Familiarity with deep learning and advanced statistical approaches to neuroimaging data Prior publications in relevant areas Required