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of Computer Science, the Technical Faculty of IT & Design. We invite applications for two fully funded PhD stipends in the area of Natural Language Processing (NLP), Knowledge Graphs (KGs), and Large Language Models
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of the UMC Utrecht is seeking an enthusiastic and ambitious PhD candidate. In this project, you will focus on developing, validating, and applying fine-grained natural language processing (NLP) and large
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international and dynamic team of researchers investigating problems in information retrieval (IR) and natural language processing (NLP) and their applications to health and medicine. The successful candidate
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administrative tasks at the Department. About the project/work tasks: The PhD project will focus on the ethical aspects of Natural Language Processing (NLP), addressing challenges such as bias, fairness, alignment
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and implementing NLP pipelines for clinical text processing, semantic annotation, and representation learning Developing embedding-based representations of clinical variables and documents to support
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learning, deep learning, and LLM-based methods to multimodal clinical datasets e.g. EHR, imaging, omics, sensor data Designing and implementing NLP pipelines for clinical text processing, semantic annotation
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and NLP for software; publish at top venues and contribute to open-source artifacts Design, implement, and evaluate prototypes that relate bug reports to code, collect lightweight runtime evidence, and
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meaningful content across languages, accurately classifying risk-related discussions, and constructing robust indicators from unstructured data. Combining modern NLP tools with financial econometric methods
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computing platforms, containerization/orchestration tools for ML workflow management and scalability. Specialized knowledge in at least one domain: NLP, computer vision, reinforcement learning, or scientific
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implementation of complex coding schemes (e.g., participation & belonging, inclusion, recognition, justice) in NLP pipelines: from guidelines/definitions to label formats to model and evaluation design. Setting up