Sort by
Refine Your Search
-
Listed
-
Country
-
Program
-
Employer
- University of Oslo
- University of South-Eastern Norway
- Oak Ridge National Laboratory
- University of Inland Norway
- University of Stavanger
- Université Gustave Eiffel
- ;
- Aalborg University
- CNRS
- Carnegie Mellon University
- Chalmers University of Technology
- Jönköping University
- King Abdullah University of Science and Technology
- Nanyang Technological University
- Nature Careers
- SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
- Technical University of Munich
- University of Cambridge;
- University of Oxford
- Aarhus University
- Barnard College
- CRANFIELD UNIVERSITY
- Centro de Engenharia Biológica da Universidade do Minho
- Charles University in Prague
- Cranfield University
- ELETTRA - SINCROTRONE TRIESTE S.C.P.A.
- FAPESP - São Paulo Research Foundation
- Faculdade de Medicina da Universidade do Porto
- Faculty of Polymer Technology / Fakulteta za tehnologijo polimerov
- Fraunhofer-Gesellschaft
- Grenoble INP - Institute of Engineering
- Institute of Photonic Sciences
- MACQUARIE UNIVERSITY - SYDNEY AUSTRALIA
- Macquarie University
- Northeastern University
- Northern Alberta Institute of Technology
- Old Dominion University Research Fountation
- Open Society Foundations
- Rutgers University
- Sandia National Laboratories
- Stanford University
- Technological University Dublin
- The University of Arizona
- The University of Memphis
- University of British Columbia
- University of California, Merced
- University of Newcastle
- University of Nottingham
- University of Texas at Austin
- University of Turku
- Université Marie et Louis Pasteur
- Vanderbilt University
- 42 more »
- « less
-
Field
-
experience with composite processing techniques such as vacuum infusion, compression moulding or hand lay-up. · Practical experience with polymer resin formulation or synthesis, particularly in dynamic
-
implementations for compression, heterogeneous quantization, etc - reproduce state of the art network parameters with extreme quantization and compression of parameters - design and implement next-generation
-
-constrained platforms such as FPGAs, Raspberry Pi, or similar embedded hardware is essential. Familiarity with model compression, quantization, or hardware-aware AI optimization techniques is a strong advantage
-
); - Experience with data balancing techniques; - Desirable basic knowledge of Multiple Input, Multiple Output (MIMO), Fluid Antenna System (FAS), and Compressive Sensing (CS); - PhD degree obtained within the last
-
Experience with responsive biomaterials (mechanical, piezoelectric, dynamic compression environments) Experience with immunomodulatory systems (e.g., macrophages, PBMCs) Understanding of biomaterial–immune
-
characterization of plant fibers by using a robot with a small tip that can compress the plant fibers one by one. These works demonstrated the capability to efficiently generate experimental tests but, we now want
-
energy-efficient cooling technologies for cryogenic temperatures (<70 K). At such low temperatures, conventional refrigeration technologies based on gas compression become inefficient or impractical, as
-
and deployment settings. Apply and advance model compression techniques, including quantization, pruning, knowledge distillation, low-rank adaptation, and related methods. Conduct algorithm-hardware co
-
-edge research in LLM. Responsibilities Develop high-efficiency, small-to-medium LLMs optimized for the edge through advanced compression, quantization, and distillation. These techniques empower resource
-
, accumulated deformations, and their impact on structural performance, particularly for compression members. Develop data-driven reusability assessment platforms integrating NDT data, machine learning models