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, with applications ranging from scientific research to medical imaging and marketing analysis. With the ever increasing amount of learning data, these algorithms face computational challenges
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curricular evaluation purposes, proven skills in programming, preferably Python; machine learning and artificial intelligence; language models and retrieval-augmented generation (RAG); ASR/TTS; diarisation
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or development pipelines; technical documentation; scientific publications or reproducible artefacts; and analytical ability, autonomy and communication in an R&D team context are particularly relevant. It is
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