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sciences, or related disciplines Strong programming skills (preferably Python and C/C++) Expertise in bioinformatics of networks Proven ability to publish in leading international journals Excellent
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cloud processing (e.g., CloudCompare, Autodesk ReCap) and/or GIS. Immersive simulation environments and interactive design tools. Experience coordinating interdisciplinary research projects. Experience in
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or machine learning methods to tackle predictive questions. Proficiency in building and validating statistical methods and/or machine learning techniques in R or Python are also essential. Applicants
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expertise in analysing/ training models on biological or chemical datasets Proficiency in Python for data science and machine learning Possess sufficient breadth or depth of specialist knowledge with deep
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Experience in statistical or scientific programming (ideally R and/or Python) Experience in analyzing large and/or complex datasets Interest in quantifying uncertainties for computer models and/or climate
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Requirements: A completed doctoral degree in chemistry, bio technology or a related field. Strong programming skills in Python, R, or similar languages. A track record of research competence and initiative
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(python, C++, bash scripting…) for the modelling of molecular crystals. To work closely with other experimentalists in the consortium and support experiments through computations. To help develop and build
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English. Programming skills (e.g. Python, R). Ability to work in teams and high social/communicative skills. Strong interest in planning, carrying out, and presenting independant research. High commitment
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thermal analyses, XRD and solid-state NMR. To develop and implement coding tools (python, C++, bash scripting…) for the automation of MoSS characterisation To work closely with other experimentalists in
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coding experience (both Python and C/C++), and a record of working in a Linux environment and related scripting languages. What we offer At the university of Oxford your happiness and wellbeing at work is