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: OBJECTIVES | FUNCTIONS The candidate will work on the development of novel approaches for clinical natural language processing specifically looking at: (a) the use of language models for coding multilingual
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of the Project GROW-LC - I3AC003101, supported by INESC-ID, is now available under the following conditions: OBJECTIVES | FUNCTIONS The main objective is to develop a model capable of performing a statistical
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domains. The successful candidate will: Develop algorithms to model team performance based on interpersonal (e.g., monitoring, communication) and cognitive (e.g., shared mental models) processes. Design an
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activity since COVID-19 with a focus on descriptive models to capture shifts in blood supply dynamics for new insights, as well as predictive models for context-aware forecasting to guide tactical and
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the following tasks: -Finetunning a Language Model for retrieval of questions related to the Portuguese Consumer Law. -Use of a Large Language Model to generate explanations of Portuguese Consumer Law that best
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the following tasks: -Finetunning a Language Model for retrieval of questions related to the Portuguese Consumer Law. -Use of a Large Language Model to generate explanations of Portuguese Consumer Law that best
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the impact on the predictive quality of a given model that is expected by retraining/fine-tuning it using additional datasets, as well as on predicting the expected cost/latency of such retraining/fine-tuning
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demand for elastic and scalable cloud resources keeps growing, as evidenced by the emergence of popular cloud computing models such as Serverless. Since this demand cannot be met with existing
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Full Professor / Researcher Técnico ULisboa / INESC-ID Member Sara Oliveira Postdoctoral researcher NKI Member Jaime Cardoso Full Professor FEUP Substitute member Mário Figueiredo Full Professor
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. Responsibilities include designing bioinformatics workflows, processing molecular data, training machine learning models, biological interpretation, and working in a collaborative international environment. BINDING