Sort by
Refine Your Search
-
Listed
-
Employer
- ;
- Cranfield University
- ; The University of Manchester
- University of Nottingham
- ; Swansea University
- ; University of Birmingham
- ; EPSRC Centre for Doctoral Training in Green Industrial Futures
- ; Newcastle University
- ; University of Leeds
- ; University of Southampton
- ; University of Sussex
- ; University of Warwick
- ; Cranfield University
- ; Imperial College London
- ; Loughborough University
- ; University of Bristol
- ; University of Exeter
- ; University of Nottingham
- ; University of Plymouth
- Harper Adams University
- 10 more »
- « less
-
Field
-
the development of system software. Key questions include how LLMs can support programmers in writing complex logical code, generating high-quality tests, and optimizing performance. Moreover, when integrated with
-
still hampered by: Ability to detect areas along the intertidal for optimal restoration3. Knowledge on how positive species interactions can be harnessed for rapid restoration4. Availability of devices
-
reliability and operational efficiency. Determining the optimal size and location of PSTs within a network is inherently complex due to the nonlinear and dynamic nature of power systems, necessitating the use
-
, scalability, and adaptability to various applications such as autonomous systems, IoT devices, and wearable technologies. Research Focus Areas: 1- Neuromorphic and AI-Optimized Processors: Design AI-specific
-
the development of system software. Key questions include how LLMs can support programmers in writing complex logical code, generating high-quality tests, and optimizing performance. Moreover, when integrated with
-
to optimize metagenomic workflows across sample types, developing integrated, sample-specific methodologies. Collaborating with leading academic developers and front line metagenomics users, including
-
project offers a unique opportunity to develop a cutting-edge genomic epidemiology toolkit for real-time fungal surveillance. You’ll optimize DNA extraction protocols using advanced enzyme-based methods
-
frameworks to ensure the developed processes are compliant, scalable, and environmentally responsible. Multiobjective optimization algorithms will be employed to balance key performance indicators such as
-
on Artificial Intelligence (AI), Deep Reinforcement Learning (DRL), and Predictive Maintenance for optimizing wind turbine performance and reliability. This research will develop an AI-powered wind turbine
-
; EPSRC Centre for Doctoral Training in Green Industrial Futures | Bath, England | United Kingdom | 16 days ago
. The research will be computational based, and at this stage is still broad, so we can formulate the optimal plan for the right candidate. We will take an interdisciplinary approach, and you will be able