Ulster University has announced that it will lead a major multi-million research project designed to harness the power of big data to better inform public policy and improve health and wellbeing outcomes across Europe. The Meaningful Integration of Data, Analytics and Services (MIDAS) project was awarded over 4.5 million euros in funding from the European Union’s Horizon 2020 programme (http://www.midasproject.eu/).

The Ulster University led project will develop a pioneering digital platform for healthcare policy makers. This will allow these decision-makers to tap into unstructured and unconnected healthcare data to better inform policy, reduce costs and improve health and wellbeing of the population. The MIDAS platform will investigate connecting patient data from European health authorities with individual data collected from apps, sensors and social media.

Globally, populations are ageing; by 2050 it is estimated that more than 2 billion people will be aged over 60 years. This demographic shift has been accompanied by an increase in cognitive dysfunction which ranges from mild cognitive impairment to dementia. Certain dietary patterns or nutritional components are recognised to have a beneficial role, thus offering potential strategies to prevent or delay the onset of cognitive dysfunction in ageing.  It has been estimated that a 5-year delay in the onset of cognitive dysfunction would reduce the population prevalence projections for dementia by 50%, which would have significant implications in terms health resources and for society generally, this PhD will begin by looking closely at this problem and the data. Small but effective dietary modifications could have major impacts on the quality of life of older people and their families. We will utilise data and perform new analysis on samples from the TUDA (Trinity, Ulster, Department of Agriculture Study) study, a unique resource designed to assess nutrition and ageing in 5,186 adults aged 60-102 years recruited from the island of Ireland. All participants have had their cognitive function assessed using 3 separate tests of cognition (Mini-Mental State Exam, Frontal Assessment Battery and the Repeatable Battery for the Assessment of Neuropsychological Status) and biomarkers of metabolic health status. The TUDA and subsequent VALID datasets are potential large heterogeneous nutritional time series data sets, if connected could offer great opportunities for piloting and development of a Data Mining platform, virtual data connection layer to identify and extract correlations and patterns between the (poly)phenols and cognitive function and markers of metabolic health.

Consequently, this PhD involves novel solutions to aggregating heterogeneous time series datasets into a comprehensive platform, using data from the existing TUDA cohorts and data to be generated as part of the VALID project. The platform will provide effective time series interrogation, analysis of patterns and drift along with visualisation of results allowing the discovery of patterns and trends that are of pertinent to public health analysis. It will involve using APIs, new approaches to heterogeneous data management and integration, new approaches to data mining and using effective data visualisation.

For additional information, entry requirements and fee details please follow: https://www.ulster.ac.uk/research/phdresearch-degrees/other-studentships

For queries please contact:

Dr Michaela Black ([email protected] )

Procedure

For more information on applying go to ulster.ac.uk/research

Apply online ulster.ac.uk/applyonline

Interviews will be held in March 2017

source:jobs.ac.uk