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Field
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excitations in nanoscale structures (e.g. methods of computational chemistry) or related techniques. Programming skills (e.g., Python, Matlab, FORTRAN, C, C++) Will to learn new techniques and approaches
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- statistical techniques used in spatial data analysis - scientific programming, e.g. Matlab, R, Python or Julia - designing and/or conducting field measurement campaigns in atmospheric
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)/machine learning (ML) applications in the power grid. * Experience with power system modeling, simulation, dynamics and/or optimization, phasor and electromagnetic transient (EMT)-based modeling, and Python
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measures for comparing hearing performance between ANI and CI users. Create and maintain software tools for stimulus delivery, response collection, and data analysis (MATLAB and Python). Collaborate with
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@au.dk) Applicants must have a relevant PhD degree in biology, biogeochemistry, hydrology, glaciology, oceanography, geoscience or physics. Field experience, data analysis and programming (e.g., python
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programming languages such as Python, R, or MATLAB for data analysis and algorithm development. Knowledge of machine learning techniques and statistical modeling for environmental applications. Excellent
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applications Proficiency in programming and data analysis languages (LabVIEW, Python, MatLab, OriginPro, JMP, or similar) Knowledge of ferroelectric materials and their properties Advanced knowledge of complex
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variables. Programming experience (e.g. Matlab, Python). A demonstrable interest in atmospheric physics and offshore wind turbines. Good organizational skills and ability to work independently. Good command
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lab/field validation. - Strong DSP/algorithms and real-time control; proficiency in Python/Matlab. - Experience integrating optics with electronics and firmware. - Track record of publications in fiber
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transport models, electrodialysis process models, or models of other desalination processes; programming in Python, MATLAB or other mainstream programming languages Demonstrated ability to publish high