PhD Studentship in Machine Learning and Artificial Intelligence University of Warwick Warwick Medical School and Warwick Manufacturing Group

Qualification Type: PhD Location: Coventry Funding for: UK Students, EU Students Funding amount: £15,009 per annum Hours: Full Time Placed On: 8th July 2019 Closes: 26th July 2019 This exciting PhD studentship based at Warwick Medical School will explore how machine learning and artificial intelligence techniques can inform emergency and critical care decision-making, and apply these methods to large clinical datasets. The proposed project is driven by evidence that clinicians find that making decisions about critical care interventions challenging, and that there is wide variability in decision-making between clinicians. Examples of these decisions include cardiopulmonary resuscitation and decisions about admission to critical care. A key reason for this is the absence of validated tools to support decision-making. The availability of large electronic datasets has the potential to enable machine learning and artificial intelligence techniques to inform critical care practice through development of decision-support tools, particularly in relation to decision-making about the likely effectiveness of treatments. This is the focus of this PhD studentship. To ensure that the student benefits from both clinical and methodological expertise, the studentship will be jointly supervised by academics from Warwick Medical School (Professor Gavin Perkins and Dr Keith Couper) and the Centre for Applied Artificial Intelligence, Warwick Manufacturing Group (Professor Giovanni Montana, WMG). Warwick Medical School and Warwick Manufacturing Group have international reputations for delivering high quality and impactful research. This innovative and inter-disciplinary studentship will also provide opportunities to work with regional healthcare providers. The successful student must have a strong background in statistics or other relevant discipline (e.g. computer science/ engineering) and demonstrable programming skills. To apply for this studentship, please apply at https://warwick.ac.uk/fac/sci/med/study/researchdegrees/howtoapply For further information, please contact Dr Keith Couper- k.couper@warwick.ac.uk The planned start date for this studentship is March 2020. Funding Details This studentship covers full tuition fees at the UK/EU rate and an annual stipend (£15,009 - 2019/2020 - RCUK stipend rate) for 3 years. If you apply for this position please say you saw it on Computeroxy Apply

Qualification Type: PhD
Location: Coventry
Funding for: UK Students, EU Students
Funding amount: £15,009 per annum
Hours: Full Time
Placed On: 8th July 2019
Closes: 26th July 2019

This exciting PhD studentship based at Warwick Medical School will explore how machine learning and artificial intelligence techniques can inform emergency and critical care decision-making, and apply these methods to large clinical datasets. The proposed project is driven by evidence that clinicians find that making decisions about critical care interventions challenging, and that there is wide variability in decision-making between clinicians. Examples of these decisions include cardiopulmonary resuscitation and decisions about admission to critical care. A key reason for this is the absence of validated tools to support decision-making.

The availability of large electronic datasets has the potential to enable machine learning and artificial intelligence techniques to inform critical care practice through development of decision-support tools, particularly in relation to decision-making about the likely effectiveness of treatments. This is the focus of this PhD studentship.

To ensure that the student benefits from both clinical and methodological expertise, the studentship will be jointly supervised by academics from Warwick Medical School (Professor Gavin Perkins and Dr Keith Couper) and the Centre for Applied Artificial Intelligence, Warwick Manufacturing Group (Professor Giovanni Montana, WMG). Warwick Medical School and Warwick Manufacturing Group have international reputations for delivering high quality and impactful research.

This innovative and inter-disciplinary studentship will also provide opportunities to work with regional healthcare providers. The successful student must have a strong background in statistics or other relevant discipline (e.g. computer science/ engineering) and demonstrable programming skills.

To apply for this studentship, please apply at https://warwick.ac.uk/fac/sci/med/study/researchdegrees/howtoapply

For further information, please contact Dr Keith Couper- k.couper@warwick.ac.uk

The planned start date for this studentship is March 2020.

Funding Details

This studentship covers full tuition fees at the UK/EU rate and an annual stipend (£15,009 - 2019/2020 - RCUK stipend rate) for 3 years.

If you apply for this position please say you saw it on Computeroxy

Apply