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Field
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inference and natural language processing. A central challenge when drawing causal conclusions from observational data is adjusting for confounding factors. In the social sciences, many of these factors
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-augmented generation (RAG) approaches Systems and mathematical modeling of biological or complex systems Natural language processing and machine learning Data harmonization and integration Record of research
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, working closely with the Core Outcome Measures in Effectiveness Trials (COMET) Initiative. You will develop and evaluate natural language processing and machine-learning methods (including large language
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Researcher in Paleomagnetism and Tectonics (f/m/d)) Geodynamics Group, Institute of Earth Sciences The Geodynamics Group investigates the processes that shape Earth′s lithosphere across spatial and temporal
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Education Required: A PhD degree in biomedical informatics or computer science. Required Qualifications: Prefer research experience in natural language processing. No working experience is required
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hold a PhD degree in the field of physics, optical engineering, biomedical engineering, electronics, or a related field on the start date of the contract. LanguagesPOLISHLevelMother Tongue
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in using natural language processing (NLP) methods on large-scale text data. Candidates with substantial experience in NLP and text-based analysis will be particularly well suited to the project
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or quantitative methods. We are open to a range of methodological backgrounds, including digital trace data analysis, natural language processing, machine learning, experimental design, causal inference, and
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studying autobiographical memory, identity, trauma, or narrative processes. - Knowledge in Natural Language Processing (NLP) or experience in interdisciplinary collaboration with computer science is a
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to colleagues and proactive. You possess excellent written and oral English communication skills. You are willing to participate actively in the intellectual life of the Radboud Center for Natural Philosophy