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with coding, ideally in Python or MATLAB Funding support This studentship is open to Home students only. It is jointly supported by the Faculty of Engineering and industrial partners which is expected
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techniques (e.g. StarCCM+, OpenFoam, Matlab, LabView, Rhino, PIV, openwater, cavitation, noise tests.). Prior research experience in propeller, wind/tidal turbine design and optimisation is highly desirable
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field. A background in organic chemistry, and/or high-throughput experimentation is desirable. Proficiency in programming languages (Python/MATLAB) commonly used in machine learning applications is
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: • Experience with programming (Python, MATLAB), • background in aerospace, computer science, robotics, or electrical engineering graduates, • hands on skills in implementation of fusion
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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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•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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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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/robotic systems Ability to implement control and kinematics with hardware-in-the–loop Background with relevant packages, (MATLAB, SolidWorks/Creo, ROS/ OpenCV/ python, LabVIEW/C languages) A driven
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packages, (CREO/SOLIDWORKS, ANSYS/ABAQUS, MATLAB) •A driven, professional and self-dependent work attitude •Experience of working within industry will be an advantage •The ability to produce high-quality