29 parallel-computing-numerical-methods research jobs at UNIVERSITY OF SOUTHAMPTON in Uk
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conditions. Our work combines traditional statistical methods with advanced artificial intelligence algorithms to identify patterns in disease. We also use qualitative methods to understand lived experiences
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organisations, in partnership with the National Centre for Research Methods (NCRM) and the Office for National Statistics (ONS). Its objective is to deliver a step-change in survey research to ensure that it will
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We are seeking to appoint a 3-year Research Fellow within the School of Mathematical Sciences at the University of Southampton in the research programme “Mathematical Foundations of Intelligence
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range of experimental methods including experimental cognitive psychology, psychopharmacology, psychophysiology and neuroscience methods to better understand the aetiology and treatment of mood and
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Experience of using qualitative and quantitative research methods Proven ability to organise a range of high quality research activities to deadline and quality standards Experience of managing and undertaking
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to gender—and demonstrated expertise in advanced statistical methods (e.g., multilevel modelling). The successful candidate will work closely with the Principal Investigator, Dr. Verena Klein, a PhD student
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We wish to appoint a Research Fellow/Senior Research Assistant for a duration of four months full time/part time equivalent to work within a research team to conduct a mixed methods evaluation of
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We are seeking a highly motivated post-doctoral researcher of high calibre to join our research program in the area of integrated silicon photonics. The position is funded by the EPSRC (Engineering
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. Application procedure This post is suitable for psychologists or data managers with a strong background in quantitative research methods and statistics and is available now. For additional information/informal
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The University of Southampton are seeking to appoint a fixed term research fellow to facilitate and deliver a programme of research on a Faraday Institution funded project: SL2FBat - Sustainable Low