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reactions, catalyst surfaces and interfaces, reaction mechanisms, activity and selectivity develop reproducible atomistic simulation and high-throughput workflows using Python, ASE and relevant DFT software
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in the development of machine learning models using Python and pytorch expertise in two or more of the following technical areas: implementation of signal processing systems, data collection
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using tools such as LabVIEW, Python or MATLAB. Pre-employment checks and declarations Your employment is conditional upon the successful completion of all pre-employment or background checks required
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science, statistics, biomedical engineering or a related field strong programming skills in R or Python experience working with spatial omics data, histopathological data, or related large-scale biological datasets
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discipline strong programming skills in R or Python experience developing or applying methods to complex or large-scale datasets ability to work both independently and collaboratively within
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-quality research appropriate to career stage evidence of a developing research profile, including publications record in a relevant field strong programming and computational research skills, such as Python
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conferences, and student awards/prizes in statistics (for instance) familiarity with statistical software, preferably with R and/or Python demonstrated ability to work independently and as part of a team with
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at seminars and conferences, and student awards/prizes in statistics (for instance) familiarity with statistical software, preferably with R and/or Python demonstrated ability to work independently and as part