171 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "Simons Foundation" positions at University of Birmingham in United Kingdom
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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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. Experience in coding (e.g., Python/R/Matlab) and experience in behavioural experimentation, statistics, or machine learning is desirable but full training will be provided. Interviews for this studentship
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. The PhD will combine behavioural experiments, machine learning, and explainable-AI methods to answer questions: Do SR techniques improve human face identification accuracy? How do SR-enhanced images affect
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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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team (https://www.cancergrandchallenges.org/rewire-can ). REWIRE-CAN will explore how novel signalling activators can be used to directly kill cancer cells (hyperactivation lethality) and/or transition
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precision immunotherapy strategies to improve patient outcomes. More information about the research group can be found here: https://www.kcl.ac.uk/research/shankar-hari-group-1. The groups’ programmatic work
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Trials - https://rarediseasetrials.org.uk/ . The project director is Professor Timothy Barret (https://www.birmingham.ac.uk/staff/profiles/cancer-genomic/barrett-timothy ), Professor of Paediatrics and
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on the project can be found here: https://hecustom.eu/ This post will contribute to the creation and validation of a digital twin (with biological bone models) to assess and interrogate the issue of