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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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models; Participation in the implementation and execution of laboratory tests for validation of the platform's algorithms, interfaces, and subsystems; Support in the analysis of experimental results and in
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to support tasks 1 and 2 of the project and includes: 1. culturing and maintaining cells under different oxygen levels and assessing their adaptation through monitoring of target proteins by western blot; 2
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while protecting data privacy. Unlike traditional centralized machine learning, where data must be collected and stored in a central server, FL allows multiple parties to collaboratively build a global
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solid, porous bioadsorbent composite with high adsorption capacity for phenolic compounds Evaluation of adsorption efficiency Study of different desorption and recovery methodologies for the phenolic