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Field
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contribute to patents or technical innovations. Qualifications: PhD in Artificial Intelligence, Machine Learning, Data Science, Electrical Engineering, or a related field. Strong experience in developing and
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-performance or cloud computing environments. Need strong data management and database skills, expertise in clinical phenotyping ontologies and the application of machine-learning/AI methods to biomedical data
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-performance or cloud computing environments. Need strong data management and database skills, expertise in clinical phenotyping ontologies and the application of machine-learning/AI methods to biomedical data
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, BLIP), fine-tuning large language models for clinical NLP, and self-supervised contrastive learning—the models will learn to effectively combine visual and textual information. By developing
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of possible methodological components include self-supervised temporal representation learning for large volumes of unlabeled AE/electrochemical time-series data, switching state-space models that describe
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: Using big data insights to optimise the manufacturing process The second phase of this project will focus on processing and utilising machine-learning techniques to analyse large volumes of data from
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developments in sensor design, dataset transmission, data analysis, and numerical modeling to distinguish between normal and abnormal features. Here, the goal is to develop machine learning algorithms
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expertise in research and development in the following areas of AI and Data Science : Machine and deep learning, NLP, BDI (Belief-desire-intention) systems, and Large Language Models (LLMs). Expertise in
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well as familiarity with machine learning workflows, natural language processing (NLP), and text-as-data methods. We are especially interested in applicants who demonstrate a strong substantive interest in using
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-focused , contributing primarily to one of the following projects: Project A – Synthetic Data for Theory-Driven Behavioral Research This project investigates how large language models (LLMs) produce