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(REA) through EU Call HORIZON-WIDERA-2023-TALENTS-01: We are looking for applications for the following role: - Research PhD fellowship on novel microfluidics and machine learning tools for unravelling
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Learning and Computer Vision Objetives: This work aims to study, develop and implement computer vision methods to detect and classify areas with imaging alterations from MRI and CT scans
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attending an academic Bachelor’s degree in the scientific field mentioned above. Knowledge or experience (preferred) on machine learning or computer vision techniques, and interest in developing such skills
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, LiDAR ) and minimal experience of five years with SAR remote sensing (Sentinel-1; ALOS-PALSAR and NISAR); - Experience in forest modeling; - Experience in machine learning algorithms, inference
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a wider ERA Chair team in interdisciplinary aspects such as microfluidic design and machine learning, however it is anticipated upon completion of the PhD the candidate will be positioned as a world
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 26 days ago
will develop computer vision, machine learning and control algorithms for a robot to perform packaging tasks. Human demonstrations will be used to generate data for learning. These data will encompass
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 26 days ago
establish reference performance and guide the design of more advanced models. The core of the work will then focus on developing and evaluating machine-learning-based NILM methods tailored
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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 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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, 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