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in a Computer Science BSc. Preferential factors: • Solid knowledge of Knowledge Representation and Reasoning Systems. • Solid knowledge of Neural Networks. • Research experience in the relevant areas
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technologies, agri-food, industry 4.0, and smart grids. This high level of knowledge transfer is achieved through both competitive research projects and direct contracted research. Therefore, public and private
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life issues, such as healthcare, space, mobility, human language technologies, agri-food, industry 4.0, and smart grids. This high level of knowledge transfer is achieved through both competitive
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. This high level of knowledge transfer is achieved through both competitive research projects and direct contracted research. Therefore, public and private entities have access to a pool of knowledge
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knowledge transfer is achieved through both competitive research projects and direct contracted research. Therefore, public and private entities have access to a pool of knowledge, resources and services
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. The candidate should also have knowledge of research work in the area of neurodegenerative diseases, particularly Alzheimer's disease, demonstrating knowledge of the use of in vitro models. Knowledge
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reasoning tasks. The work aims to develop a similar framework (methodology) but relying on analogy based reasoning, a powerful inductive mechanism, widely used in human cognition and increasingly applied in
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, in collaboration with the team responsible for the development of the ApneaScreener algorithm. Knowledge of data analysis tools, particularly Python and R, will be valued to support the interpretation
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-operation with aquaculture companies in the Dsolve consortium in order to gather data for further analyses. The elected candidate must be able to start in the position within a reasonable time after receiving
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knowledge related to the work plan (30%); - Criterion 3: Adequacy of the candidate’s profile to the work plan to be developed (20%); - Criterion 4: Motivation letter (10%); VII.II- The evaluation