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change to delivery of health services. Experience with large datasets and excellent communications skills will be essential for this role. This role will involve developing and applying analysis plans
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, develop novel approaches for proving hardness, and devise new algorithms. You will be expected to conduct individual research and develop research questions, regularly write research articles at a national
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Learning or Machine Learning algorithms Experience applying quality system standards, software development standards and regulation, e.g. ISO 13485, IEC 62304, MDD, and MDR Experience working within a team
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for proving hardness, and devise new algorithms. You will be expected to conduct individual research and develop research questions, regularly write research articles at a national level for peer-reviewed
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Intelligence for Humanity. Research – As a part of the Dyson School of Design Engineering, you will actively develop and lead your own research programme, in line with our research themes and vision. You will be
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About Us We are seeking experts in medical image deep learning to join our team and help develop novel computationally efficient segmentation algorithms. We welcome application from individual with
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with the regulatory environment around Deep Learning or Machine Learning algorithms Experience applying quality system standards, software development standards and regulation, e.g. ISO 13485, IEC 62304
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deep learning to join our team and help develop novel computationally efficient segmentation algorithms. We welcome application from individual with experience in: Deep learning Medical imaging computing
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bioinformatics Previous experience with AI and/or machine learning approaches Interest in reproductive health and/or development of clinical tools and algorithms Downloading a copy of our Job Description Full
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bioinformatics Previous experience with AI and/or machine learning approaches Interest in reproductive health and/or development of clinical tools and algorithms Downloading a copy of our Job Description Full