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the medium and long term. We are looking for a Machine Learning Research Engineer: The ideal candidate will bring deep expertise in state-of-the-art deep learning methods applied to computer vision, 3D
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databases. Design, implementation, and testing of deep learning and AI algorithms for processing tabular, genomic and temporal data. Where to apply Website https://www.uam.es/uam/investigacion/ofertas-empleo
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/Mey 24G8b1X Deadline for submission of applications: 19 December. TITLE OF THE POSITION OFFERED: Research and Development in Machine Learning for smart cities. SUBJECT AREA: Computer Science. TYPE
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multidisciplinary team spanning hydrology, machine learning, ecological flows, and water resources management.The selected candidate will join the IberianCAMELS research team as a Predoctoral Researcher, contributing
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apply machine learning algorithms with special attention to digital footprint reduction and data privacy. Functions to be developed: Develop methodologies and experiments to measure and optimize
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Electrical Machines (a second-year course of the Bachelor’s Degree in Electrical Engineering, 4,5 ECTS credits, code 44221), as well as in other related subjects offered by the school. Additionally
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(Mandatory): Machine Learning Statistical Modeling Data Visualization Academic Writing Languages (Mandatory): English: IELTS 7.0 or higher LanguagesENGLISHLevelExcellent Research FieldComputer science
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physicsEducation LevelMaster Degree or equivalent Skills/Qualifications A Master’s Degree in Physics or similar. Specific Requirements Experience in big-data management and analysis, with solid machine learning
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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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integrations, and collaborating with the team to refine detection strategies and performance metrics. Tasks to be performed Literature review on scam detection, blockchain security, and machine learning methods