Sort by
Refine Your Search
-
Listed
-
Field
-
harvesting recent breakthroughs in Machine Learning (ML) and analytical modelling. Specifically, this project seeks to quantify key performance metrics and create powerful adaptive ML-driven management methods
-
with NEOM, one of the world’s largest ecological restoration programmes, the project will develop machine-learning approaches to analyse satellite observations of vegetation change and evaluate large
-
framework integrating physics-informed machine learning, scenario generation, and human-in-the-loop preference-based reinforcement learning to prioritise climate-robust and equity-aligned interventions
-
network integration for emerging low-energy opto-electronic AI systems and beyond. The challenge: Machine learning and neural networks are super-charging the complexity of problems that computer algorithms
-
machine-learning-based surrogate models to accelerate design and control workflows. This PhD studentship would suit candidates with backgrounds or interests in engineering, physics, applied mathematics
-
geolocated social media data, and computational techniques from network science and machine learning. It is interdisciplinary, combining theories of healthy and accessible cities with computational data
-
, adaptive control strategies, and hybrid energy storage solutions to address key challenges in self-powered systems under dynamic environmental conditions by: Develop machine learning or heuristic-based