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administrators, and patient advocates—who bring deep domain knowledge without necessarily having technical expertise. You will play a key role in designing and implementing research projects, analysing data, and
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, computer science, data science, or similar · Strong publication record in peer-reviewed conferences and/or journals · Experience applying machine learning methods (especially deep neural network approaches
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aspirations and development goals. Job Requirements: Essential Criteria Close to completion or hold a relevant Ph.D. with post-qualification research experience in statistical machine learning, and deep
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, single-cell analysis, and machine/deep learning (preferred but not required). Strong programming and statistical skills (e.g., Python, Perl, R, Bash). Track record of first-author research papers. Strong
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, computational, and machine learning/AI methods, with a particular emphasis on deep learning approaches improve our understanding and prediction of infectious disease dynamics. Projects are also strongly grounded
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SIT's mission is centred on nurturing industry-ready graduates who possess deep technical expertise and transferable skills to address future challenges. We collaborate with industry in our
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discipline. Experience and deep understanding of X-ray scattering experiments Experience with development of analysis code for experimental data in Python or similar language Strong interest in learning new
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Fellow in EEE to contribute towards NLP-based research and associated deep learning applications. The Research Fellow/Research Associate is also expected to support teaching activities as required by
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from date of hire. Preferred Qualifications Aptitude and experience with: (a) predictive machine and deep learning techniques, (b) statistical analysis, (c) hands-on experience using models such as
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platform that utilizes deep learning to analyze images of bruises. Responsibilities: Responsible for developing components of the project platform or deep learning application; Supervises a team of graduate