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discipline such as Bioinformatics, Proteomics, Metabolomics, or Analytical Chemistry, and have a strong track record in LC-MS platforms, particularly with the TQ-XS triple quadrupole instrument. You will bring
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relevant discipline. For the Grade 7 positions, you will have an emerging track record of delivering research projects on time and are nationally/internationally respected in your field. For the Grade 8
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implementation, and applications are welcome across these areas of expertise. About you As a Teaching and Research Fellow, you will have a proven track record of conducting excellent research and a growing
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approaches to scholarship. A proven track record of peer-reviewed publications and a demonstrable commitment to research impact and community engagement will be essential. Prior experience of research related
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purification of mammalian membrane proteins for Cryo electron microscopy. You will have a proven track record in conducting high quality research, an ability to work both independently and as part of a team, and
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milestones and objectives. They will perform specialised assays for testing novel drug candidates and will help with laboratory running, ordering reagents and consumables for the project, organising
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proficiency in distributed and high-performance machine learning algorithms, methods for exploiting modern system architectures for high-performance AI, and quantum distributed computing. A proven track record
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research methodologies. A proven track record of contributing to peer-reviewed journal publications is essential, along with analytical problem-solving capabilities. Expertise in relevant biological models
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will have expertise in qualitative research, with experience in conducting systematic or narrative reviews. A proven track record of research productivity, demonstrated through peer-reviewed publications
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synthesis, NMR, mass spectrometry, and enzymology. A proven track record of research productivity, evidenced by publications in peer-reviewed journals and presentations, is essential. Knowledge