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We have 374 data quality PhD Projects, Programmes & Scholarships

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data quality PhD Projects, Programmes & Scholarships

We have 374 data quality PhD Projects, Programmes & Scholarships

Integrated omics approach to psychiatric disorders

  Research Group: Chemistry and Biosciences
In psychiatry, the selection of antipsychotics and antidepressants is led by a trial-and-error approach. The prescribing of these medications is complicated by sub-optimal efficacy and high rates of adverse drug reactions (ADRs). Read more

Trusted-Edge and Semantic-based Approach for Dependable IoT and Smart Systems

The integration of sensors and embedded devices for the purpose of data acquisition to support human activity recognition, management of living challenges, and behavioural patterns for the purpose of proactive decision making has continue to open more direction of research in smart home applications such as Ambient Assisted Living (AAL). Read more

Metabolomic characterisation of adiposity across the life course

There is evidence that adiposity, measured by body mass index (BMI), causally influences a range of health outcomes, but little understanding of the mechanisms driving BMI effects. Read more

Metabolomic characterisation of adiposity across the life course

Project Background. There is evidence that adiposity, measured by body mass index (BMI), causally influences a range of health outcomes, but little understanding of the mechanisms driving BMI effects. Read more

Cloud XR QoE for Programable Networks: Understanding how to deliver high-quality immersive XR experiences over future programmable networks.

Cloud rendered immersive Extended Reality (XR) has many applications across consumer, enterprise, and industry domains. Cloud gaming enables consumers to play immersive games on a variety of client devices by streaming content rendered from remote GPU servers. Read more

Optimal prediction of dynamical systems with incomplete data

Dynamical systems describe a variety of real-life problems related to evolution over time. It is often the case that the problems are so complicated that mathematical models for them either do not exist or are not accurate enough. Read more

Data-driven optimal prediction of bacteria growth

This project is devoted to an AI-based prediction of bacteria growth and its control by antibiotics. In synthetic biology, an improved understanding of bacterial regulatory circuits is required to develop complex biological systems with functionalities beyond existing in nature [1, 2]. Read more

PhD in Chemistry - Taking Crystal Sponges into the Nanoscale Using 3D Electron Diffraction

Bright, highly motivated candidates are invited to apply for a fully funded 3.5 year PhD position in the School of Chemistry, available to commence on 1st October 2024 in the Forgan research group at the University of Glasgow, which will focus on the use of electron diffraction to characterize metal-organic frameworks and probe new applications such as the nanoscale crystal sponge technique. Read more

Towards a better understanding of indoor air quality in the home

The World Health Organisation (WHO) recently stated that exposure to indoor and outdoor air pollution was one of the greatest risks to human health, and that improving air quality was necessary to reduce the global incidence and impact of diseases such as lung cancer, stroke, and asthma. Read more

Mitigating the impact of environmental stress on the quality and sustainability of malting barley

Climate change is challenging our ability to reliably grow crops. This PhD will be focused on the impact this is having on our capacity to produce a sustainable supply of malted barley for use within the brewing and distilling industries. Read more

Data-driven optimal prediction of bacteria growth

This project is devoted to an AI-based prediction of bacteria growth and its control by antibiotics. In synthetic biology, an improved understanding of bacterial regulatory circuits is required to develop complex biological systems with functionalities beyond existing in nature [1, 2]. Read more

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