University of Dundee

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Characterisation of enhancer DNA methylation and its impact in gene expression and disease

The School of Life Sciences at the University of Dundee is a world-class academic institution with a reputation for the excellence of its research, its high quality teaching and student experience, and the strong impact of its activities outside academia. With 900 staff from over 60 countries worldwide the School provides a dynamic, multi-national, collegiate and diverse environment with state-of-the-art laboratory, technology and teaching facilities.

MRC DTP 4 Year PhD Programme: Cell stress patterns and pathways in the mammalian embryo

Exposure to toxins from the environment has been linked to a rise in non-communicable diseases and behavioral deficits in adults. WHO data further indicate that deaths attributable to environmental factors are highest in children. Metabolic stress during embryonic development is also correlated with increased risk of type 2 diabetes, coronary artery disease and cancer as well as some psychiatric illnesses.

BBSRC Eastbio PhD Programme: The role of E3 ligases on the modulation of recombination in cereals

In barley and wheat substantial proportions of the chromosomes are inherited together as a large linkage block, preventing the generation of novel gene combinations and useful variation that could be exploited in breeding and genetics programs. In these crops, the distribution of meiotic crossover events is skewed toward the telomere regions meaning that up to half of the genes rarely if ever recombine.

MRC DTP 4 Year PhD Programme: Discovery of composite biomarkers and the role on the retina in risk prediction for systemic diseases using deep learning

Supervisors: Prof Emanuele Trucco, School of Science and Engineering, Dr Alex Doney, School of Medicine / Clinical and Molecular Medicine.

Aims and objectives. The project will use deep learning (DL) techniques to discover combinations of phenotypic and genotypic features working as predictive risk scores for high-incidence conditions (e.g. cardiovascular, diabetic complications).

MRC DTP 4 Year PhD Programme: Use of Machine Learning and Computer Vision to detect Cerebral Microbleeds in SWI MRI

Small areas of bleeding in the brain, known as cerebral microbleeds (CMB), are emerging as important features of an aging brain.  Not only are they a marker for unhealthy blood vessels associated with development of dementia, but they also indicate an increased risk of major bleeding in the brain.  This is particularly a concern in the common situation where doctors need to use medicines that stop clots from forming, and therefore increase risk of bleeding, to prevent heart attacks and ischaemic strokes.  Although CMB are common they are not checked for routinely in conventional commonly us

MRC DTP 4 Year PhD Programme: AI-Spot-Dementia (AISDA): developing machine learning algorithms to predict the risk of dementia for patients with Type 2 Diabetes

The aim of this PhD proposal is to develop novel machine learning algorithms (e.g., deep learning) to predict the risk of dementia in Type 2 diabetes, and detect early signs of such disease with association of clinical and genomic data in clinical settings. There are strong links between Type 2 Diabetes (T2D) and dementia.  With increasing numbers of people developing T2D, detecting early signs of dementia is important to better understand how it can be delayed or prevented.

MRC DTP 4 Year PhD Programme: Automatic, reliable detection of nocturnal epileptic seizures in real time via machine learning of multi-modal data.

Supervisors: (Lead): Dr Ian Morrison, Department of Neurology, Ninewells Hospital, Professor Emanuele Trucco, School of Science and Engineering, Professor Stephen McKenna, School of Science and Engineering.

Background

BBSRC Eastbio PhD Programme: Developing and applying a high - throughput platform in barley to screen for resistance and enhanced susceptibility to aphids

Aphids are economically important pests globally, and can cause significant yield loss of crops, including barley. Currently there are no commercial barley cultivars that are resistant against aphids, and only limited sources of partial resistance have been reported to date. As a consequence, control of aphids mainly relies on the use of insecticides.  In this project we aim to address the lack of available resistance in cereals to aphids pests by identifying new resistance sources in barley.

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