Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- University of Oslo
- Nanyang Technological University
- UiT The Arctic University of Norway
- Humboldt-Universität zu Berlin
- INESC TEC
- University of British Columbia
- FEUP
- Harvard University
- Indiana University
- LINGNAN UNIVERSITY
- Lawrence Berkeley National Laboratory
- Northeastern University
- Oslo University Hospital
- Queen's University Belfast
- SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
- Universidade Católica Portuguesa - Porto
- Universidade de Coimbra
- Universidade do Minho
- University of Algarve
- University of Aveiro
- University of Bergen
- University of Inland Norway
- University of South-Eastern Norway
- Virginia Tech
- Zintellect
- 15 more »
- « less
-
Field
-
and responsible human–technology and human–AI collaboration in reverse logistics operations, while demonstrating how AI can optimize production, improve data utilization, and enhance automation
-
, etc.) Whilst some metrological techniques are very robust (quantum Hall effect, Josephson effect) it remains a challenge to produce controlled sources of electrons and phonons that are critical
-
to research on some of the following themes: New algorithms for parallel/distributed AI/ML Hardware-aware and resource-efficient partitioning for parallel/distributed AI/ML Optimization of process-to-process
-
). The project focuses on experimental design, optimization, and construction of entangled and/or squeezed states of light for a range of applications. The role also involves building and setting up various
-
synthesis of timed and probabilistic behavioral models for model checking, performance evaluation, and optimization. The overall objective is to establish formal foundations that bridge static engineering
-
that integrate prediction and control algorithms, optimizing data transformations, offloading and distributed computing, and exploiting mechanisms such as network slicing and multi-access edge computing
-
, computationally expensive, model simulations. This experimental design process is envisioned to update iteratively as new data become available to optimally infer surface fluxes across the landscape. The work will
-
. The goal of the PhD will be to seek mechanistic insight into the electrode polarization processes as well as strategies for improving performance by optimization of composition, microstructure, and the
-
cloud platforms for compute and storage. Version Control & CI/CD: Git, automated testing, deployment workflows. Experience with Linux systems, HPC, and distributed computing environments. Knowledge
-
physical latency limits and human perceptual tolerances. The work will comprise designing networking and computing architectures that integrate prediction and control algorithms, optimizing data