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Post-doctoral Research Fellow in “Brain in the Wild” Methodologies - join the team!



Applications are invited for a 24-month Post-doctoral Research Fellow position as part of the NeuroInsight Marie Skłodowska-Curie COFUND Action for Postdoctoral Fellowships.

NeuroInsight is a collaboration between the FutureNeuro SFI Research Centre for Chronic and Rare Neurological Diseases and the Insight SFI Research Centre for Data Analytics.

We are interested in the development of biomarkers for chronic neurological conditions and for neurodevelopmental disorders in particular.

Our approach is the use of data analytics and machine learning in particular to develop new means of tracking the severity, progression and treatment of such disorders. We seek to apply neuroscience-informed computational models to data collected from subjects outside the laboratory, at home, during everyday living. We are interested in observing and collecting data from the human brain “in the wild”. In much the same way that researchers in movement disorders can now access data from movement sensors in our phones and in wearable fitness trackers, we use smartphones and wearable sensors for better capture of the brain at work, at play, at rest and everything in-between. This is obviously challenging and for such a project, we focus on the use of electrical measures of brain activity (electroencephalography) using dry electrode systems along with behavioural data collected via smartphones with further context collected by the phone sensors and other wearables.

We are seeking a postdoctoral researcher interested in working in this area to improve existing solutions we have in this space as well as develop new innovations for virtual clinical trials. This includes a wide range of potential project targets, ranging from improved measurement of specific biosignals via deep learning approaches for denoising, integration with home virtual reality platforms for gamification, ecological momentary assessment techniques, multimodal data capture, reinforcement learning modelling approaches to brain and behaviour data and large scale data mining and machine learning.

We have clinical collaborators and partners with whom we can co-design these methodologies such that they are deployable in impactful and effective ways for data collection. If interested, contact me for further information.


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