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/ physics/ meteorology/ engineering/ biology. Experience in a computer programming language (e.g. Fortran, Python). A general understanding of the importance of the scientific method is essential. A previous
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degree in Engineering and have an interest in and/or a good understanding of numerical modelling and testing of structures. Prior knowledge of finite element methods and programming (e.g. C++, Python
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. Strong quantitative skills, with experience in econometrics and statistical analysis. Experience working with large datasets and appropriate software (e.g., Stata, R, Python, Julia, MATLAB). Excellent
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of the following topics will be a plus: Application of machine learning to power grids/cyber-physical systems Knowledge of working with MATLAB/Python Power grid optimisation/control Experience working with power
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, training, and collaboration Preferably a strong background in aircraft design and propulsion systems Preferably Proficient in programming (MATLAB preferred; Python is also acceptable) Prior experience with
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programming with Bash and Python is also required and previous experience of vertebrate and invertebrate genomes would be beneficial. The ideal candidate will be an independent researcher capable of managing a
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Appropriate computational skills and knowledge of programming languages (Python, C++, etc.) Experience with Machine and Deep Learning models and software (Keras, Scikit-Learn, Convolutional Neural Networks, etc
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monitoring. Familiarity with tools such as Python, MATLAB, or embedded C would be advantageous. Most importantly, this project is ideal for applicants who are motivated to tackle real-world reliability
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and computational abilities • Demonstrate excellent programming ability in languages such as MATLAB or Python • Excellent communication skills across multiple disciplines • Excellent academic
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tools like FEniCS and Python. Additionally, working on a high-impact, interdisciplinary project will strengthen problem-solving, critical thinking, and project management skills. The collaboration with