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PyTorch or TensorFlow, is highly advantageous. Experience in developing and deploying machine learning models, particularly in natural language processing (NLP) and large language models (LLMs), including
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from sensors or other continuous data sources. Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages
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. Familiarity with AI algorithms and Machine Learning Fluent oral and written communication skills in English Desired qualifications: Experience with research on epidemiological modelling, with an emphasis
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for implementing the model as a computer simulation and analysing it within a health-economics framework using standard computational techniques. The post-holder will also be responsible for writing up the findings
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with epilepsy across multiple NHS hospitals. They are expected to have some experience working with NLP in general and LLMs in particular. They will also help to further develop machine learning models
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element method, wave propagation analysis, inverse problem, machine learning (ML), and artificial neural network. Strong background in research publications in the desired field. Experience mentoring other
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-scale assessment data, meta-analyses of meta-analyses) Methods and approaches to cumulative, living, and community-augmented meta-analyses Methods and approaches to include machine learning and artificial
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working with NLP in general and LLMs in particular. They will also help to further develop machine learning models to predict clinical outcomes. Familiarity with current methods in this area is essential
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. Desirable: Proficiency in scientific programming (e.g. Python) and familiarity with data science and machine learning techniques. Experience with geochemical analytical techniques and working in a laboratory
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, and AI chatbot chats; (b) quantitative content analysis; (c)text mining and machine learning methods; (d) survey design and public opinion research; (e) election studies; (f) the Norwegian political