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. Applicant should have experience in time-series processing with appropriate AI models (recurrent networks, LSTM) and experience in 2D convolutional neural networks in Python. This is a part-time position (5
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2D convolutional neural networks in Python. This is a part-time position (5 hours/week) funded until 31/03/2026 with a possibility of extension and is suitable for a Ph.D. student with relevant
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/Python and signals processing Understanding of electromagnetics Experience with CAD and mechanical design How to apply: Interested candidates should submit a full formal application, guidance and the
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. This research is ideally suited to candidates with interests in photonics, metamaterials, ultrafast optics, nanofabrication, and computational electromagnetism. Strong coding (Python /MATLAB) and experimental
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are looking for an enthusiastic individual with a degree in a quantitative discipline. Experience of geospatial analysis (with GIS) is essential and programming with code (e.g. R, Python) would be advantageous
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: Working knowledge of MATLAB/Python and signals processing Understanding of electromagnetics Experience with CAD and mechanical design How to apply: Interested candidates should submit a full formal
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will be required to demonstrate their ability to identify fundamental flow features and model these using suitable CFD methods. Experience in Fortran/C/C++/Python/Matlab is an advantage but not essential
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interest and research in the field of economic and experience in data management and analysis. Demonstrable experience of working with quantitative data and relevant software (Stata, R, Python, or similar
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interest and research in the field of economic and experience in data management and analysis. Demonstrable experience of working with quantitative data and relevant software (Stata, R, Python, or similar
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intelligence, NLP, machine learning, or a related field Experience with Python and Generative AI libraries (e.g., Huggingface Transformers) Knowledge of Multimodal Generative AI models and their corresponding