Background to the project. The aim of late phase clinical trials is to generate evidence to guide clinical practice and policy to improve health outcomes1. Read more
The overall goal of our research is to discover the circuit implementation of learning and action selection. Since these functions likely emerge from… Read more
Cancer is an evolutionary process. Cells in a tumour vary due to mutation, and so over many generations they adapt in response to both intrinsic selective pressures (such as anoxia) and extrinsic selective pressures (such as chemotherapy). Read more
Scientific background . Why do organisms age? Classical resource allocation-based theory of ageing – the so-called ‘disposable soma’ (DST) – has been challenged by empirical studies and can no longer fully account for the experimental observations. Read more
Postgraduate students in Civil Engineering conduct original research and complete a dissertation and an oral examination to earn their degree. Read more
Postgraduate students in Civil Engineering conduct original research and complete a dissertation and an oral examination to earn their degree. Read more
Project Overview. Antimicrobial Resistance (AMR) is one of the topics that we cannot ignore. Bacterial infections unsuccessfully treated due to AMR claim at least 700 000 lives per year worldwide and are projected to be associated with the deaths of 10 million people per year by 2050. Read more
The predictability of evolution by natural selection is one of the big questions in evolutionary biology. It also has enormous practical importance in crop protection. Read more
Scientific background the wider context; why the project is important and timely . Mimetic relationships - where two or more species share colour patterns to reduce attacks by predators are some of the most powerful demonstrations of natural selection. Read more
Almost every protein-coding gene in vertebrates can and does express multiple proteins. This is achieved primarily by RNA splicing, which is an essential step in gene expression in mammals and generates incredible diversity. Read more
This PhD aims to develop an adaptive self-organising solution for dynamic scheduling in job-shop manufacturing. The research will introduce an innovative approach that integrates deep reinforcement learning and multi-agent systems to rapidly respond to emergencies and disruptions. Read more
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