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-based imaging techniques (TEM, fluorescence, histology etc.) Successful grant applications Experience in Python programming Having worked on diverse science projects, in international surroundings
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wind tunnels such a temperature/pressure sensitive paints, infrared thermography, PLIF, FLDI etc. • Proficiency in Python • Experience running simulations with high performance computing (HPC) resources
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in population genetics, statistical genetics, or a closely related area. Proficiency in statistical and bioinformatics tools and programming languages (e.g., Hail, R, Python). Experience with
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, or a closely related field. Proficiency in analysing large climate and environmental datasets using statistical or programming tools (e.g., Python, R, MATLAB). Capability of both managing research
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neurogenetics of Drosophila. This requires expertise in setting up and analysing behavioural tests, using appropriate analytical methods and software and skills in coding in e.g. R, MatLab, R, Python, as required
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, and Python to process vector and raster data for agronomic decision-making - Documented experience with producing educational communications and programming - Demonstrated ability to effectively
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different numerical tools via Python scripting Experience conducting machine learning and inverse design models HPC experience Experience training and supervising students High proficiency in writing skills
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major programming language, such as Java, C/C++/C#, Python, and preferably in several languages; proficiency in the Linux operating system and deployment and configuration of virtualised environments
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. Software and programming experience may include: R, STATA, Esri Arcmap, python, Leaflet, PostgreSQL, CSS, JavaScript, JQuery, Bootstrap, PHP, QGIS, PostGIS, Mapserver, Tableau, Openlayers, Geoserver, R Shiny
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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