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, cultural practices and technologies between China and the Mediterranean or any sub-region between the two at any period up to the present day. This Research Fellowship is part of a broader programme, which
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Qualifications* PhD Degree in Engineering, Computer Science, Data Science, Applied Mathematics, Statistics, or a related field Familiarity with (biomedical) signal processing Experience working with clinical data
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. The successful candidate will become an active member of the Energy, Power and Intelligent Control (EPIC) research centre within the School of Electronics, Electrical Engineering and Computer Science (EEECS
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Position as PhD Research Fellow in formal methods for data protection in digital twins is available at the Department of Informatics. Starting date no later than December 1, 2025. The fellowship period is
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Twins Apply for this job See advertisement About the position Position as PhD Research Fellow in formal methods for data protection in digital twins is available at the Department of Informatics. Starting
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Please apply online and attach your resume (including a list of two referees), and a separate cover letter that outlines how you meet the selection criteria below: Essential Selection Criteria: PhD in
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MACQUARIE UNIVERSITY - SYDNEY AUSTRALIA | North Ryde, New South Wales | Australia | about 1 month ago
to Apply Please apply online and attach your resume (including a list of two referees), and a separate cover letter that outlines how you meet the selection criteria below: Essential Selection Criteria: PhD
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attach your CV (including a list of two referees), a statement of research interests and achievements. Essential A PhD in plant and/or microbial community ecology or a related discipline and relevant
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the role Overview of the role We are seeking a highly motivated Research Fellow in Machine Learning to join the PharosAI team, focusing on developing novel machine learning methods in computer vision
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the role Overview of the role We are seeking a highly motivated Research Fellow in Machine Learning to join the PharosAI team, focusing on developing novel machine learning methods in computer vision