Sort by
Refine Your Search
-
Listed
-
Country
-
Employer
- Monash University
- Nature Careers
- European Space Agency
- University of Sheffield
- Zintellect
- Nanyang Technological University
- Technical University of Munich
- University of British Columbia
- University of Michigan
- ;
- Carnegie Mellon University
- ETH Zurich
- Rutgers University
- Stony Brook University
- University of California
- University of California, Merced
- Yale University
- AIT Austrian Institute of Technology
- Cornell University
- Emory University
- Iowa State University
- Lawrence Berkeley National Laboratory
- Marquette University
- NIST
- Oak Ridge National Laboratory
- Pennsylvania State University
- Purdue University
- SUNY University at Buffalo
- University of Houston Central Campus
- University of Lund
- University of Michigan - Ann Arbor
- University of Pennsylvania
- University of Washington
- Washington State University
- Aalborg University
- Arizona State University
- Aston University
- Brookhaven Lab
- California Institute of Technology
- Career Education Corporation
- Colorado Technical University
- Curtin University
- East Tennessee State University
- Fairmont State University
- Forschungszentrum Jülich
- Fraunhofer-Gesellschaft
- Harbin Engineering University
- Johns Hopkins University
- Linköping University
- MOHAMMED VI POLYTECHNIC UNIVERSITY
- McGill University
- North Carolina State University
- Northeastern University
- Princeton University
- SciLifeLab
- State University of New York University at Albany
- The University of Arizona
- The University of Chicago
- UNIVERSITY OF SOUTHAMPTON
- UNIVERSITY OF SURREY
- University of Alabama at Birmingham
- University of Bristol
- University of California, Santa Cruz
- University of Colorado
- University of Florida
- University of Glasgow
- University of Kentucky
- University of Leicester
- University of Maryland
- University of Miami
- University of Nebraska–Lincoln
- University of New South Wales
- University of Oslo
- University of Phoenix
- University of Pittsburgh
- University of Texas at Austin
- University of Toronto
- University of Utah
- University of Warsaw
- University of Wisconsin-Madison
- University of the West of England
- 71 more »
- « less
-
Field
-
algorithms and complexity theory, including in both well-established settings (e.g., sequential computation on a single machine and distributed/parallel computation on multiple machines) as well as emerging
-
of distributed ML models. You will be expected to collaborate with senior engineers and researchers across domains. This role includes opportunities to work with state-of-the-art natural language processing, large
-
knowledge in FPGA design. We desire a person interested in collaborating and learning with a team of fellow brilliant researchers to develop the next level of processing and analysis algorithms, possess
-
the project to have well-distributed data both in space and time. This will ultimately lead to higher quality (more spatially and temporally accurate, complete, precise) 3D models. However due to the complexity
-
images. However, the current limitations of desktop computers in terms of memory, disk storage and computational power, and the lack of image processing algorithms for advanced parallel and distributed
-
at one time. In non-stationary environments on the other hand, the same algorithms cannot be applied as the underlying data distributions change constantly and the same models are not valid. Hence, we need
-
. This could include scholarship in topics such as, theoretical or applied data analytics; algorithm development and solving concrete problems for science, industry, and society within various application
-
and distributed control intelligence that can be applied to solve these problems through the application of machine learning, intelligent optimization techniques, automated fault detections and
-
(DevOps and CI/CD) Computer Science Topics: Programming Analysis of Algorithms Operating Systems and Distributed Systems Computer Organization and Architecture Artificial Intelligence Other related topics
-
Federated learning (FL) is an emerging machine learning paradium to enable distributed clients (e.g., mobile devices) to jointly train a machine learning model without pooling their raw data into a