Contact - Research Centre for Brain and Behaviour
Need more information about the work conducted at the Research Centre for Brain and Behaviour? Get in touch with us via the links on this page.
Need more information about the work conducted at the Research Centre for Brain and Behaviour? Get in touch with us via the links on this page.
HIV services and prevention work within the North West of England utilise the Public Health Institute's interactive tools, databases, and intelligence work. We offer assistance through evaluations and research into: contraception, teenage pregnancy, STDs, young people's health. Find out more about this aspect of research within the Public Health Institute.
Find out more about BEST's expertise in sustainable resource processing and planning.
The Applied Physiology Nutrition and Metabolism Group within RISES are involved in health, wellbeing, recovery and sporting performance. Our research into exercise metabolism and adaptation is applicable to the design of interventions that improve human health.
The Galaxy Formation and Evolution Research Group looks at population studies of dwarf galaxies up to the most massive clusters of galaxies, supermassive black holes and detailed modelling of the internal structure of galaxies. Discover more about our expertise, who we work with and meet the researchers.
‘The Six P Sustainability Framework’ is intended for organisations utilising Nature for Mental Health. It provides a structure from which a practical set of sustainability indicators have been derived and collated into a self-assessment tool.
Discover a number of resources for the Flu Vaccine campaign in multiple languages.
The RISCS (Research to Improve Stair Climbing Safety) group of RISES is looking for people over the age of 65 years to take part in a study that aims to develop a community-level screening tool that can detect the risk of a fall on stairs specifically.
Find out more about how LJMU staff and postgraduates can find and book practical, bench- and lab-based training.
Find out how our machine-learning systems are helping decision-making for transport authorities and commuters resulting in a greener, more efficient and more sustainable transport and logistics.