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Field
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annotations or NLP methods (for example, by automatically identifying named topics and positive attitudes or negative towards them). These important resources require, however, in their construction
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with Python, JavaScript, and SQL. Required Skill/Ability 2: Proven experience with large databases. Required Skill/Ability 3: Proven experience with NLP (Natural Language processing) or ML (Machine
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» OtherEducation LevelPhD or equivalent Skills/Qualifications • PhD in ML/AI, Computer Vision, NLP, or Biometrics. Excellent publication record with at least some papers in top tier venues according to ELLIS
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areas such as NLP, imaging, speech, etc. • Proficient with Python and AI related frameworks (such as scikit-learn, tensorflow, pytorch, etc.) • Knowledge in machine learning platform and services from
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(NLP), computer vision or other AI subfields. knowledge of data modelling, data processing and analysis and data integration knowledge of AGILE processes and methods good communication skills and a
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, information extraction, dialog tree generation and knowledge discovery using state-of-the-art NLP approaches. Experience with deep learning-based information retrieval, and/or deep generative natural
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engineers, and PhD students in the fields of natural language processing (NLP) and neuro-symbolic AI. You shape research agendas and technology roadmaps in exciting areas of deep learning based NLP and neuro
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: Extraction, cleaning, exploration, and analysis of data collected from various sources, including organizational data and aggregated intelligence; Model creation and implementation using methods such as NLP
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: Natural language processing (NLP) Large language models and generative AI Machine leaning Data analytics General data protection and privacy regulation Technical competencies Knowledge of relevant technical
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information, using Machine Learning and Natural Language Processing (NLP) techniques, in particular: Survey of necessary and not adapted requirements of the solution that will integrate the analytical and