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Automated Program Repair (APR) is the grand challenge in software engineering research. Many APR methods have shown promising results in fixing bugs with minimal, or even no human intervention
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that unveil the unseen. analyse complex data to uncover insights and pioneer new strategies for molecular sensing and imaging. We’re looking for someone who brings: A PhD in chemical biology, organic chemistry
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formula is true or false (EXPTIME vs NP). Can we develop and implement efficient algorithms for this problem? This problem has been attacked using multiple different methods for the past 40 years, without
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through supervision of PhD students, and contribute to the educational and administrative duties of the Department and Faculty such as by taking on course direction roles. As the successful candidate, you
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bring demonstrated analytical skills, a track record of peer-reviewed publications and experience in data extraction for systematic reviews or meta-analyses. Strong proficiency with software tools such as
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in diverse, real-world environments. Both classical machine learning methods and deep learning techniques can be employed to tackle this task. This project aims to achieve several objectives: 1
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statistical software Knowledge of Good Clinical Practice requirements and adherence to research guidelines Experience conducting research involving participants with chronic health conditions If you're ready to
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closely with academic staff and provide guidance and support to junior researchers and students involved in the project. Ideally you will have a PhD in Economics of Education or expect to receive it by
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, conferences, or equivalent textbooks/teaching resources Ability to lead outstanding research and manage a research team and projects Demonstration of effective PhD or Honours student supervision Proven success
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proven record of relevant teaching experience in a tertiary environment, including experience in developing teaching materials. A deep understanding of contemporary pedagogies and methods is essential