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Field
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health tools. Basic proficiency in data analysis (Python or R); experience with speech analysis libraries or NLP is an asset. Strong scientific writing skills and a collaborative spirit. High motivation
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. Whilst full training will be given, previous experience with tissue culture, analysis of genomics data, bioinformatics approaches or previous use of relevant platforms such as R, are desirable
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. Strong quantitative skills, with experience in econometrics and statistical analysis. Experience working with large datasets and appropriate software (e.g., Stata, R, Python, Julia, MATLAB). Excellent
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bioinformatics, especially Python and/or R are required Experience from relevant research projects investigating cellular metabolism, and/or protein modifications and signalling, respectively, will be considered
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into commercial R&D, and participate in government and industry working groups. Impact and Career Development This project aligns with EPSRC and University strategic priorities in energy, decarbonisation, and AI
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experience working with cohort data or electronic health records is an asset; Interest in digital health and diabetes research; Proficiency in R and/or Python; Excellent writing and communication skills in
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-months during the whole period) at Port Sunlight, supervised by Steph Edwards and Andy Peers, during which time they will be able to access world-leading facilities across the Port Sunlight R&D and
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also undertake industrial placement and mentorship at BTS, where they will interact with practitioners, gain insights into commercial R&D, and participate in government and industry working groups
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biochemistry are required Profound knowledge in bioinformatics, especially Python and/or R are required Experience from relevant research projects investigating cellular metabolism, and/or protein modifications
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statistical data evaluation, creation of scientific programme codes using common software packages (MATLAB, Python, R) Simulation skills with e.g. molecular dynamics and alpha fold Knowledge