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record will demonstrate proficiency in the design, fabrication, and pre-clinical testing of innovative devices. You should be adept with LabView, Matlab, and SolidWorks. About the School The role will be
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downconversion layer Analysis of data using software tools such as MATLAB, Python, or Origin. The candidate must be familiar with materials studio software and any other materials modeling software. Experience in
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in developing engines and/or fuel cells models in GT-Power. Experience in using MATLAB/ Python/Siemens Simcentre to develop AI-assisted programme and models for powertrains and propulsion systems
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medical challenges. Previous experience in programming (MATLAB/Python/C/C++) and image processing is preferred. Knowledge in machine/deep learning and high-performance computing is a plus but not required
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implemented in the Fortran programming language, and it relies on the platform CUDA for parallelization of the computation over several GPUs’ cores, and has interfaces with Matlab and Python for ease of use
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Experience with signal processing, statistical data analysis, or machine learning techniques. Proficiency in scientific programming (e.g., Python, MATLAB, or similar). Ability to work independently while
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coding experience with e.g. Python/Matlab/R Practical experience with High Performance Computing, and scientific programming and a willingness to learn to work with high-performing computing systems
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response windows) and balance metrics using appropriate software (e.g. MATLAB, EEGLAB, BrainVision Analyzer). Manage research data in line with ethical and GDPR standards, including anonymisation, secure
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++, ROS, Matlab, etc.). You should have a strong vision to evaluate and demonstrate the research findings in real life operating conditions, in an approach to close the gap between pure theory and
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, or a closely related field. Proficiency in analysing large climate and environmental datasets using statistical or programming tools (e.g., Python, R, MATLAB). Capability of both managing research