12 genetic-algorithm-computer "Integreat Norwegian Centre for Knowledge driven Machine Learning" Postdoctoral positions at King's College London
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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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6. Desirable criteria Evidence of active collaboration with dry lab and co-development of algorithm for the prediction of epitopes. Downloading a copy of our Job Description Full details of the role
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for more information. About you To be successful in this role, we are looking for candidates to have the following skills and experience: Essential criteria 1. PhD degree in Engineering, Computer
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strengths in laboratory-based enquiry using molecular genetics, metagenomics, biochemistry, cell biology, bioinformatics and structural biology, with rich clinical resources in microbiology, virology
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. Advanced microscopy, cutting-edge biophysical techniques and genetically engineered mouse models will be used. The labs are well-established and located in the vibrant and supportive environment
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diabetes; genetics; infection and immunology; imaging and biomedical engineering; transplantation immunology; pharmaceutical science; physiology and women's health. We also have thriving research programmes
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Putts; and inflammatory genetics. The successful candidate will support other researchers and MSc/PhD students. They will develop novel scientific questions and lead on the analysis of specific aspects
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” of the brain is genetically determined, it is also influenced by environmental experience. We are still far from a complete understanding of how these processes work. CDN is one of four departments in the School
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clinicians and computational scientists. This project will be supervised by Prof Oscar Marin and Prof Beatriz Rico. Candidates should have strong experience in stereotaxic surgeries and Electrophysiology
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well as clinical phenotyping in participants. The work will involve close collaboration with other team members, driving the programme on aetiopathology of neuropsychiatric disease forward. It will also involve