|Funding for:||UK Students, EU Students, International Students|
|Funding amount:||at least UCL minimum|
|Placed On:||10th January 2023|
|Closes:||4th April 2023|
Transforming Clinical Brain Imaging to Protect the Neonatal Brain.
Primary Supervisor: Ilias Tachtsidis
Secondary Supervisor: Subhabrata Mitra
Subsidiary Supervisors: Paola Pinti
A 4 year funded PhD studentship is available in the UCL Department of Medical Physics and biomedical Engineering Biomedical Optics Research Laboratory in collaboration with University College Hospital (Neonatology) and EGA Institute for Women’s Health and the worlds first ToddlerLab at Birkbeck. Do also check out Prof. Tachtsidis Public Engagement team website metabolight for further info.
Funding will be at least the UCL minimum.
The successful candidate will join the UCL CDT in Intelligent, Integrated Imaging in Healthcare (i4health) cohort and benefit from the activities and events organised by the centre
The first 2 years of life are critical for the development of the neural connections and functions responsible for normal motor and cognitive functioning in humans. Perinatal injury to the developing brain often refers to as birth asphyxia, continues to remain a significant cause of neurodevelopmental disability.
We need objective, non-invasive, hospital and outpatient clinic friendly, easy to operate brain imaging tools to inform early detection of newborn brain injury; to support neurobehavioural interventions in young infants and toddlers, ultimately leading to the best possible brain development.
To answer this need, this PhD will build upon technological advancements in brain imaging and computational techniques; these include (i) magnetic resonance spectroscopy (or MRS) that can quantify bioproducts of metabolism; (ii) optical imaging, with broadband near-infrared spectroscopy (or bNIRS) and diffuse correlation spectroscopy (or DCS); a non-invasive brain imaging instrument that can map cortical oxygenation, haemodynamics, blood flow and metabolic changes from birth; and (iii) machine learning approaches for classification and prediction of newborn brain injury.
The ambition of this project is to innovate neuroimaging and redefine what can be investigated in the developing brain of infants at risk of neurodevelopmental disability.
The objectives of this PhD project are:
A first degree in physics or engineering would be preferred, however candidates from other potentially relevant backgrounds (e.g., psychology, medicine or neuroscience) will be considered if they can show the right level of commitment and interest.
A full studentship is available for Home fee applicants.
Overseas fee payers will be considered but they must have secured a separate scholarship that can cover the fee difference between Home Fee and the Overseas fee.
UCL’s fee eligibility criteria can a be found by following this link.
Deadline: 4th of April 2023
Type / Role: