Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- University of Cambridge;
- Delft University of Technology (TU Delft)
- Fundació per a la Universitat Oberta de Catalunya
- Hasselt University
- Iquadrat Informatica SL
- KU LEUVEN
- NTNU Norwegian University of Science and Technology
- University of Bergen
- University of Newcastle
- University of Nottingham
- University of Oslo
- University of Texas at El Paso
- 2 more »
- « less
-
Field
-
developing a collection of spatially distributed models for these objectives within an encoder-decoder framework to reduce the dimensionality, enabling the use of multi-objective optimisation to generate a
-
communication skills in English, excellent presentation, organisational and problem-solving skills. Self-motivated to achieve research objectives and ability to work effectively and independently as part of a multi
-
an analytical-computational framework for a “living” 4D Digital Twin (3D + time) to enable automated progress monitoring and multi-domain safety assessment in civil engineering applications. The project focuses
-
details can be found at https://www.net-zero-fibe-cdt.eng.cam.ac.uk/ The project is funded in collaboration with Network Rail, the entity responsible for the operation and maintenance of the Great Britain's
-
during a 1976 style drought event by tracking key measures of water system performance, specifically determining how effectively today’s system and operational rules would manage a modern 1976-type drought
-
. It will seek multi-objective optimization (sound insulation, sound absorption, and electricity generation) aiming to integrate renewable-energy technologies into sustainable acoustic design. Focusing
-
the network-management level, it delivers AI/ML-driven, multi-objective, user-centric orchestration for CF-mMIMO to improve overall energy efficiency by 20%, a decentralized compute-orchestration framework
-
spectral and energy efficiency by 2× in uplink and 3× in downlink; finally, at the network-management level, it delivers AI/ML-driven, multi-objective, user-centric orchestration for CF-mMIMO to improve
-
. GENMAR’s research objective is situated at the intersection of these three knowledge gaps. The project will develop a multi-sited, multi-scalar, comparative and theorized ethnography of gender inequality
-
and the spread of delays, which will underpin a proposed multi-objective optimisation approach for enhancing resilience and efficiency. Benefits of joining this project: This project will give an