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within a Research Infrastructure? No Offer Description Work Plan: • State-of -the-art survey in language models (LLMs), vision and language models (LVLMs), and trusted AI. • Establishment of the model
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). The content of their studies are closely related to the research areas of SECAI. This includes but is not limited to studies in the following programmes: - MSc Computational Modeling and Simulation (TUD) in
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component. The work to be developed by the student will involve extracting information from unstructured clinical text using Large Language Models (LLMs), with the goal of developing Trust worthy models. More
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phenomenological model considering the kinetics of the methane splitting reaction (function of temperature, pressure, and catalyst), and the residence time and type of flow. iv) Development of the lab pilot plant
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Annotation for Training AI Models 2. Development and Optimization of AI Models for Fraud Detection 3. Implementation of an AI Model for Stock Management of Current Dispensers 4. Implementation of a Distributor
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Funds are available to pay the fees of a MSc by Research in Medical and Health Care Studies for a student working on a project that seeks to produce a zebrafish model of episodic ataxia. Ataxia is a
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, the work plan includes: Exploratory Data Analysis of unstructured data related to lung cancer patients. - Extraction of structured data with Medical Language Models. - Development of explainability
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of unstructured data related to lung cancer patients. - Extraction of structured data with Large Language Models. - Development of explainability mechanisms for the component to be developed. - Publication
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. - With experience in: a) ROS, Programming in C++, Python, Ladder; b) 3D modeling and CAD/CAM programming; Specific Requirements Master in Electrical Engineering or similar enrolled in a PhD course or a non
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/F) Call open for applications for a research grant within the framework of project 2022.06672.PTDC – iMAD - Improving the Modelling of Anomalous Diffusion and Viscoelasticity: solutions to industrial