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Field
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correction and/or mitigation. Knowledge about networking protocols and distributed algorithms. Experience in programming, e.g., in C++, Python or Matlab. Experience with quantum simulators, such as NetSquid
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statistics of mean and extreme wind events over the Baltic Sea region. Tellus A, 67, 29073. https://doi.org/10.3402/tellusa.v67.29073 Björkqvist, J.-V., Lukas, I., Alari, V., van Vledder, P.G., Hulst, S
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highly advantageous: Scientific programming in Python or MATLAB Probabilistic methods, Bayesian inference, or stochastic modelling Structural mechanics, material modelling, or multi-physics simulation Data
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: Scientific programming in Python or MATLAB Structural mechanics, reliability analysis, or probabilistic modelling Data analytics, SHM/SCADA data interpretation, or digital-twin technologies Wind energy systems
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wind energy systems. In particular, experience in one or more of the following areas will be considered highly beneficial: Scientific programming in Python or MATLAB Structural mechanics, reliability
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of advanced wind turbine components. Experience in one or more of the following areas will be considered highly advantageous: Scientific programming in Python or MATLAB Probabilistic methods, Bayesian inference
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• Data visualization solutions (i.e. Power BI, Tableau, Google Data Studio) for producing reports • MATLAB/PYTHON/R/C programming • Application of Machine Learning Algorithms Selection process Please
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/Computer Engineering, Computer Science, Applied Maths or related. Strong skills in AI techniques/ML/optimisation (Python/Matlab); familiarity with probabilistic modelling, time-series or control/power
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, including REDCap along with experience in research compliance and administrative management systems. Experience in Python, R, and MATLAB for data analysis. Experience in administering and developing fMRI and
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techniques (punctuation: 20) Item 03: Experience in experiments with lampreys or other basal vertebrate models (punctuation: 15) Item 04: Experience using programming tools (Matlab/Python) for data analysis