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Field
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science and FAIR practices (through software, datasets and other research outputs, participation in challenges etc). Familiarity with knowledge engineering methodologies and with semantic technologies, in
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metabolism and human physiology. Experience with clinical research and/or experimental medicine studies necessary. Analytical Skills: Proficiency in data analysis and statistical software. Experience with high
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datasets and demonstrate familiarity with statistics software packages, such as Stata and Python. Knowledge about computer text analysis is also desirable. Excellent written communication skills are required
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response windows) and balance metrics using appropriate software (e.g. MATLAB, EEGLAB, BrainVision Analyzer). Manage research data in line with ethical and GDPR standards, including anonymisation, secure
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processing software Experience in prokaryotic (E.coli) cell culture Experience in eukaryotic (e.g. HEK293T cells and/or insect cell systems) cell culture Experience in basic molecular biology and biochemistry
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response windows) and balance metrics using appropriate software (e.g. MATLAB, EEGLAB, BrainVision Analyzer). Manage research data in line with ethical and GDPR standards, including anonymisation, secure
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, software and techniques such as qualitative data analysis using NVivo. Possess sufficient breadth or depth of knowledge (sociology of place), to work within established research programmes. Research
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; supervising student projects/practicals. · Demonstrable ability to model experiments using a range of software packages, such as Python, Matlab or Mathematica. · Experience of experimental
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methods and analytical tools in Africa and Asia. Our protocols and software will be available to the community to allow wider testing and sustained implementation. A critical part of WaSPP research agenda