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Predoctoral Researcher (PhD Candidate) in Computational Simulation and AI for Therapeutic Ultrasound
• Strong academic record • Good English level • Programming skills in Python and/or MATLAB are desirable Selection will be based on academic excellence, suitability for the project and research potential
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: · Working knowledge of MATLAB/Python and signal processing · Basic understanding of electromagnetics · Experience with CAD and mechanical design How to apply: Interested candidates should contact Dr Hungyen
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proficiency in data analysis (with a preference for experience in advanced techniques, though it's not mandatory). Proficiency in programming (e.g., Python or MATLAB) is advantageous. Strong communication
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of experience in Wireless DSP and have extensive knowledge of radar and/or communication systems. You are fluent in MATLAB or Python. Ability and willingness to obtain Security Clearance (National, EU, NATO) – a
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Numerical methods Programming skills (Python, MATLAB, or similar) Strong analytical and problem-solving skills. Good written and spoken English. Desirable: Experience with photonic/electromagnetics design
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relevant discipline. Experience with modelling or simulation tools (e.g., MATLAB/Simulink, PSCAD, PowerFactory, or Python) is desirable.
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: • Knowledge of fluid dynamics, especially experimental methods in atomisation and sprays. • Programming experience (e.g. Python, MATLAB or similar). • Experience with data analysis, machine learning
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physiology. Experience with molecular cloning, bacterial strain engineering or fermentation is a plus. Data analysis skills (e.g. Python, MATLAB) or experience with metabolomics and mass spectrometry are a
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. Programming experience in at least one language such as Python, MATLAB, or C/C++. Strong analytical, quantitative, and problem-solving skills. The ability to work effectively both independently and as part of a
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, RocScience, ...) Knowledge of scripting or programming languages (e.g. Matlab, Python, R ...) Experience in automated processing of remote sensing data and time series analyses Strong interest and basic