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Field
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Description Implement and validate machine learning models and statistical algorithms for data imputation, anomaly detection and uncertainty management in geospatial environments. Collaborate in the preparation
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learning. Professional Experience: Have worked using Machine learning. Programming in C, C++. Experience in functions similar to those described will be valued, specifically in the development of research
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(Machine Learning Force Fields, ML-FF) to simulate gas-phase fragmentation processes via molecular dynamics. Design and maintain a project-focused results database (schema, metadata, upload/retrieval scripts
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: Machine and Deep learning. In health and rehabilitation projects. Experience in functions similar to those described will be valued, specifically in the development of research activities, both in
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measurements. Professional Experience: In health and rehabilitation projects. Classification and models of Artificial Intelligence: Machine and Deep Learning. In recording and signal processing. Experience in
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processing (computer vision & machine learning) Where to apply Website https://sede.uvigo.gal/public/catalog-detail/28364578 Requirements Research FieldEngineering » OtherEducation LevelMaster Degree
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. SILEX 2025) to calculate the Fire Radiative Power (FRP) and compare with satellite observations (VIIRS, SLSTR, FCI). Develop a fire front segmentation algorithm using machine learning techniques (deep
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of multimedia datasets (voice, text, etc.). Development of predictive models for cognitive impairment and Parkinson's disease using signal processing and machine learning techniques. Development and debugging
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networks and in mobile & edge computing platforms. Where to apply Website https://networks.imdea.org/job/phd-position-on-safe-machine-learning-msca-final… Requirements Research FieldEngineering » Electrical
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fields. Relevant Training or Courses (optional): Experience with R or similar programming tools, or machine learning algorithms. Geographic Information Systems (GIS). Basic and advanced statistics, time