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estimates, and collaborating with various billing departments, specialty clinics, hospitals, and health centers on all related billing concerns. Works independently and efficiently to assist families
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-based transfer learning classification model for two-class motor imagery brain-computer interface. International Journal of Neural Systems (IJNS). https://doi.org/10.1142/S0129065719500254 * Kudithipudi
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: Developing adaptive haptic training strategies that help operators refine their skills through real-time skill estimation, multimodal feedback, and tailored trajectory guidance. Enhancing Robot Autonomy
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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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problem aims at estimating model parameters from input data, having access to a model describing how to generate the observations if the parameters to estimate were known. For instance, in optical remote
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Two-year postdoc position (M/F) in signal processing and Monte Carlo methods applied to epidemiology
and data-driven procedures for pointwise and/or credibility interval estimation of epidemiological indicators, e.g., for the reproduction number R(t) of Covid19. Elaborating on a recent epidemiological
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such as: Systems security, Security engineering, Security testing, Computer forensics, AI for security and privacy, Security and privacy of AI. Our department addresses computer science challenges from a
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Qualifications Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Artificial Intelligence, or a related discipline. Strong interest in 3D computer vision and machine learning methods
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are seeking to recruit a Senior Research Fellow to work on the development and implementation of methods for improving small area modelled human population estimates. The successful candidate is expected
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Website https://www.inesctec.pt/en/opportunity/AE2025-0570 Requirements Specific Requirements Academic qualifications: Currently enrolled in an ongoin Bachelor's degree in Computer Engineering or Electrical