102 machine-learning "https:" "https:" "https:" "https:" "https:" positions in Portugal
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, or similar) will be valued; 9) Experience in machine learning techniques applied to materials science or process engineering (regression, classification, optimization, predictive models) will be valued; 10
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Grant Regulations. Where to apply Website https://apply.uc.pt/ Requirements Research FieldEngineering » Computer engineeringEducation LevelBachelor Degree or equivalent Additional Information Work
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of the suitability of the profile for the functions and tasks to be performed focuses on the candidate's experience in machine learning and COMSOL modelling of materials and devices. Note: These criteria will be
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using machine learning; Interpretation of soil profiles and moisture maps. Development and validation of digital tools: Support in building georeferenced web interfaces for data visualization
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river valleys); • Identify stylistic patterns and regional variations in schematic rock art; • Apply machine learning tools for large-scale stylistic classification; • Establish a robust chronological
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will develop a new high-precision digital twin for WDS based on a self-calibrated hydraulic model with a machine learning correction model and, together with advanced data analytics, will detect and
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study cycle or non-award courses of Higher Education Institutions. Preference factors: Programming experience in Python; Knowledge of machine learning and computer vision Minimum requirements
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than 14/20 (1 point); B. Knowledge of Interactive Systems Design, Cyber-Physical Systems, Predictive Maintenance Systems, Automation, Machine Learning and Artificial Intelligence, Sensor Networks
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for applications for one research grant within the framework of project ISA4RL - Integrating Instance Space Analysis with Auto-Reinforcement Learning for Adaptive Algorithm Selection and Configuration
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Machine Learning components of the CONVERGE project toolset.; - Assist in executing integration tests across different hardware and software modules.; - Contribute to the structured collection and