14 machine-learning "https:" "https:" "https:" "https:" "https:" "Dana Farber Cancer Institute" scholarships at University of Birmingham
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records that can systematically inform preparedness, training and future response. As a result, learning from past events is fragmented, inconsistently captured, and insufficiently embedded into emergency
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data set (e.g. neutron irradiations, that take years/decades to generate). Digilab brings AI/ML (artificial intelligence / machine learning) approaches for data engineering and automation to utilise
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systems and tools to respond using an ‘all hazards’ approach. For more information, please see: https://www.birmingham.ac.uk/research/centres-institutes/nihr-health-protection-research-unit-in-emergency
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applicable across emergency preparedness and response settings. For more information, please see: https://www.birmingham.ac.uk/research/centres-institutes/nihr-health-protection-research-unit-in-emergency
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testing, flight dynamics and control. How to apply: The application will be made through the university’s online application system (https://sits.bham.ac.uk/lpages/EPS024.htm). Please provide a cover letter
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information, please see here: https://www.birmingham.ac.uk/research/centres-institutes/nihr-health-protection-research-unit-in-emergency-preparedness-and-response Supervision team: Dmitri Nepogodiev (Associate
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, eligibility is restricted to UK nationals. Informal enquiries are encouraged and should be directed to: Dr Richard Horniblow, r.horniblow@bham.ac.uk https://www.engineered-microbiome.co.uk/
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Programme grant can be found at https://oncoeng.org/ Funding notes: The PhD project is funded through a University of Birmingham, School of Engineering PhD scholarship which provides maintenance
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programming (e.g., Python/C++), machine learning frameworks, or robotics software environments such as ROS. You are motivated to work in a multi-disciplinary research environment combining engineering, AI, and
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Reniers, who bring expertise in the areas of human computer interaction and psychology respectively. The PhD student will be co-supervised by DfT’s Behavioural Science team, work alongside DfT teams at key