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for An enthusiastic, self-motivated individual with an interest in empirical and modelling work to test out new reactor designs. This will involve some work with Matlab or similar program to quantify mixing systems
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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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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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•Background with relevant packages, (CREO/SOLIDWORKS, ANSYS/ABAQUS, MATLAB) •A driven, professional and self-dependent work attitude is essential •Experience of working within the industry will be an advantage
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driven research Maths competency and experience with statistics in research Software competency: ImageJ, Matlab, Graphpad Prism, R Evidence of Github use An interest in cardiovascular physiology
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with programming (Python, MATLAB), background in aerospace, computer science, robotics, or electrical engineering graduates, hands on skills in implementation of fusion/learning based techniques in
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Experience Experience developing research software using appropriate languages and environements (Python, Julia, Matlab) Knowledge of optimisation problem formulations and solution methods Experience of risk
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in applied mathematics, or a closely related subject with substantial mathematical content. Skills in programming (MATLAB, Julia) and numerical bifurcation theory (e.g. DDE-BIFTOOL, MATCONT