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: Prior experience in modelling & programming tools such as SINCAL, PowerFactory, OpenDSS, PSCAD, Python, Matlab, R, or Julia would be desirable. For full details about this role, please review the Position
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numerical analysis or modelling of (palaeo)environmental data using R/python/Matlab or similar platforms. Experience with sediment analysis, which may include palaeoecological techniques, sedimentology
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confidence and a proven track record using common coding languages (e.g., Python, Matlab, Fortran) expertise and a publication track record in numerical geoscience modelling, such as, but not limited to plate
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Postdoctoral Research Associate in Global Environment Modelling of Soil Organic and Inorganic Carbon
or a related discipline, with an emphasis in numerical computation intermediate to advanced skills in large data analysis and manipulation, including programming in different languages including Matlab
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experience with coding in Matlab, Python, or R. Strong track record in computational science, image analysis, or mathematical modelling of complex systems. Evidence of publications in reputed refereed journals
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such as for example Superconducting Quantum Interferometers and Cavity Magnonics Interferometers. Ability to maintain and develop tools for more advanced experiments by using Python, MATLAB, COMSOL and
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software (Prism, Origin Pro, Matlab etc) A good understanding of appropriate statistical analysis techniques Qualifications Mandatory: PhD or equivalent in relevant field. Please Note: Appointment to
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atmosphere models Strong background in mathematics, physics, engineering or related field Experience in scientific computing, including C/C++, fortran, python, or MATLAB Version control and package management
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). Proficiency in numerical modelling, data analysis and instrument control in languages such as Matlab, Python, C/C++, etc. Familiarity with sensor technologies and applications, machine learning, and electronics
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, Python, SAS, MATLAB). A commitment to high-quality curriculum development, course coordination, and inclusive, student-focused learning. A developing research profile with potential for collaborative