Cosmology as a Relational Dynamical System
Dr D Sloan
Applications accepted all year round
Cosmology models the behaviour of our universe in terms of a small set of descriptive variables; the scale factor, Hubble parameter, relative shear expansions etc.
Enhancing predictability in chaotic systems
Dr F Ginelli, Prof A Politi
Applications accepted all year round
The goal of this research program – which involves theoretical analysis and numerical simulations -- is to apply fundamental results and recent developments (to which the supervisors significantly contributed) of dynamical system theory to enhance our ability to predict the future evolution of complex and chaotic dynamical systems -- such as weather and climate systems.
Movement control using dynamics matching and anticipatory coupling
Prof S Nasuto, Dr Y Hayashi
Applications accepted all year round
"There is a lot of interest in explaining motor coordination and control. Such models allow for better understanding of the healthy coordination and provide diagnostic tools and starting points for rehabilitation solutions in case of motor disorders due to stroke or neural degeneration.
Flexibility provision from energy systems integration
Dr M Qadrdan, Dr C Ugalde-Loo
Application Deadline:
19 April 2019
As part of this project, novel methodologies and modelling tools will be developed to analyse integrated energy systems and optimise their operation.
Modelling rapid CO2 and climate change in the Southern Ocean
Dr A Burke, Prof D Dritschel, Dr J Rae, Dr J Reinaud
Application Deadline:
5 April 2019
The Southern Ocean plays a fundamental role in the regulation of Earth’s climate through its uptake of heat and carbon. Despite representing only 20% of the ocean surface area, it accounts for more than 50% of ocean carbon uptake and more than 75% of ocean heat uptake (Charrassin et al., 2008; Meredith and Hogg, 2006).
Dynamical Redesign of Biomolecular Networks
Dr E Rosta
Application Deadline:
26 March 2019
Project Description. We will develop novel theoretical frameworks [1] using machine learning approaches to address catalytic efficiency and to establish molecular design principles to key design problems for new bio-inspired nanocatalysts.
Neuronal Dynamics from a complex network perspective
Prof A Politi, Dr E Ullner
Applications accepted all year round
The human brain is possibly the most intriguing complex system we know. The combination of experimental work and theoretical approaches has gained many insides in the last century but we are still far away from a real understanding.
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College of Engineering Centenary PhD Scholarship: New Generation of Real-Time Response Models Based on Deep Learning
