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biology, microbiology or biochemistry Experience in Archaea research, including genomics and CRISPR-Cas systems Proactive and eager to learn new methods and topics Strong collaborative attitude in the lab
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Principal Investigator or Grant-holder and other colleagues in the research group, as appropriate, to identify areas for research, develop new research methods and extend the research portfolio. To deal with
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and other colleagues in the research group, as appropriate, to identify areas for research, develop new research methods and extend the research portfolio. To deal with problems that may affect the
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Machine Learning, Statistics, Computer Science or closely related discipline. They will demonstrate an ability to publish, including the ability to produce high-quality academic writing. They will have the
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dimensions and will examine family and family life as fundamental to the waging and experience of war. The project is interdisciplinary and will utilize mixed methods. The project will have three contemporary
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experience in: Deep learning Medical imaging computing (preferably neuroimaging) Computationally efficient deep learning Deep learning model generalisation techniques. Translating deep learning models
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between the Hong Kong Polytechnic University (HKPU) and the Royal College of Art (RCA), funded by the Hong Kong SAR Government’s InnoHK programme. Drawing on the research excellence of both institutions
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the mindfulness intervention Analysis of quantitative and qualitative data generated from the project Compiling a report to the funding body at the half way and end of the project Preparing a mixed methods article
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legal research methods Knowledge and familiarity with critical and feminist approaches to gendered violence Knowledge and familiarity with research on online environments, in particular social media
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or Sociology, and those with expertise in qualitative, historical and/or archival methods. The successful candidate’s host department will be determined according to best fit. The post holder will be responsible