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Field
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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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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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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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physiological signals, with a focus on ECG, and to develop machine learning and deep learning methods for classifying clinical, health, and wellness findings. Supporting project management and research group
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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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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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the field of Biological Engineering available within the project “Machine learning-driven CD19 CAR T cell manufacturing for improved safety and efficacy in the treatment of hematologic cancers”, Ref
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program (2025.02832.MAD), funded by FCT-Madeira, under the following conditions: I. Scientific Area: Electrical Engineering and Computer Engineering II. Admission Requirements
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of scientific computing involving machine learning models for viscoelastic fluid flows. Legislation and regulations: Law Nº. 40/2004, of 18th August, in its current wording (Statutes of Scientific Research Fellow
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interaction with the road infrastructure. • Experience in big data analysis and handling of large data sets, with skills in applying AI and machine learning techniques to traffic pattern analysis and road