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Field
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to completion) in Computational Materials Chemistry or a related discipline Experience in Defect Chemistry Analysis Experience in Python Programming Expertise in Electronic structure analysis of solids Expertise
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Epidemiology or related subject or a similar quantitative discipline. Programming skills in Python; or experience in at least one of the following: C, C++, Java, R, Matlab, and willingness to learn Python
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the appropriate area. Familiarity with statistical analysis software (e.g., STATA, R, SPSS) or computer programming (e.g. C++, Python, R) and experience working with health-related data will be advantageous
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and show strong quantitative skills, proficiency in coding (e.g. Python or MATLAB), and experience handling large datasets. Knowledge in at least one of the following is essential: ocean interior
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of using and developing Machine learning/AI based classifiers Proficiency in coding using R and Python and other similar languages High level analytical capability Ability to communicate complex information
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stakeholders (beyond academia). Experience in membrane handling, CAD and temperature/humidity control is desirable while the ability to code in Python or other related programming languages will constitute a
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tools such as R, Python, or MATLAB as well as relevant machine learning frameworks Experience in statistical data analysis, and expertise in areas such as experimental design, linear/nonlinear models
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programming using languages such as Bash, C, C++, or Python. This role meets the eligibility requirements for a skilled worker certificate of sponsorship or a global talent visa under UK Visas and Immigration
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bachelor’s degree in Economics or a related field by the start date. Good knowledge of Stata and/or Python is preferred. For further information regarding the skills required for this role please see the
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skills in Python; or experience in at least one of the following: C, C++, Java, R, Matlab, and willingness to learn Python. Experience in working with epidemiological or healthcare (or similar) data