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, with opportunities to build an international research portfolio. The post holder will work on developing and testing study design and data analysis methods, particularly related to cluster randomised
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A Master’s degree in social research or a related discipline (or nearing completion of PhD) Demonstrable experience of qualitative research methods, including conducting interviews and/or focus groups
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guidance to PhD students where appropriate to the discipline Contribute to developing new models, techniques and methods Undertake management/administration arising from research Contribute to Departmental
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for publication, research seminars etc Supervise students on research related work and provide guidance to PhD students where appropriate to the discipline Contribute to developing new models, techniques and
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annotation of these metabolomes using multistage fragmentation (MSⁿ) data, incorporating novel computational methods and strategies (e.g. spectral matching, network-based approaches, machine learning) where
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to Tackle Modern Slavery’, led by Dr Rowland Seymour. The successful candidate will join a diverse and friendly research group with PhD students and a Research Software Engineer. The goal of the project is to
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regular team meetings Supervise students on research related work and provide guidance to PhD students where appropriate to the discipline Contribute to developing new models, techniques and methods as
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for publication, research seminars etc Supervise students on research related work and provide guidance to PhD students where appropriate to the discipline Contribute to developing new models, techniques and
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for publication, research seminars etc Supervise students on research related work and provide guidance to PhD students where appropriate to the discipline Contribute to developing new models, techniques and
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on research related work and provide guidance to PhD students where appropriate to the discipline Contribute to developing new models, techniques and methods Undertake management/administration arising from