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undergraduate degree in a relevant computational domain, such as engineering, physics, neuroscience, computer science, applied mathematics. Skills in computer programming (especially Python or C++ or Matlab) and
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understanding of motor drive control. • Experience of using Matlab/Simulink, PLECS, C Language. • Excellent organisational, communication and team working skills. Through the Knowledge Transfer Partnership
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understanding of power electronics with hands-on experience • Basic understanding of motor drive control. • Experience of using Matlab/Simulink, PLECS, C Language. • Excellent organisational
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proficiency in Python (e.g., NumPy, Pandas, scikit-learn, PyTorch, TensorFlow); additional experience with R, MATLAB, or Julia is an advantage. Machine Learning Expertise: Familiarity with supervised
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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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, alignment, and characterisation of laser-based instrumentation. • Strong experience with computer programming, both for signal processing and experimental hardware control (e.g., C, C++, Python, MATLAB
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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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•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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/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