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- Universidade de Coimbra
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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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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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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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, 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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, and any formalities established there must be fulfilled until the time of signing the contract. Activity Outline: • Design and modeling of new supports with internal cooling, exploring additive
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, resulting in technical specifications for the demonstrator model. Monitoring of Tests and analysis of Test results. Legislation and regulations: Law Nº. 40/2004, of 18th August, in its current wording
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of the University of Coimbra (FMUC), a group that has been studying EVs as a therapeutic platform; and by the Animal Bioscience group at the University of Évora, with very relevant experience in a large model for
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assignment of a research grant, with one position(s), under the project COIMBRA ST LLM_EUI02-188:Large Language Models applied to create better experiences for tourists and local communities whilst supporting