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Field
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of videos/images already collected in a real environment at the Hospital da Misericórdia da Mealhada and which will be made available; definition of accuracy and latency metrics. 3) Implementation and
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for clinical AI based on patient data from heterogeneous sources notably language/speech-based sources. The activity will focus on the development of a prototype implementation of early warning- and other AI
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optimizations, such as new data caching algorithms. Develop a prototype that integrates the optimizations and experimentally evaluate the prototype.; Integrate the optimizations with a new modular and flexible I
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. The awarding of the fellowship is dependent on the applicants' enrolment in study cycle or non-award courses of Higher Education Institutions. Preference factors: Previous experience in biomedical image and
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storage devices; - Implementation of a prototype of the previous system and design of profiling mechanisms that enable identifying complex I/O patterns and the corresponding placement rules; - Experimental
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time experiments. Experience of working in an interdisciplinary team. Experience with supervising and mentoring more junior researchers. Beneficial Criteria Experience in coding (e.g. Python, C, Fortran
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photographic documentation. Production of derived visual content: Generation of renders, animations, and illustrative images from 3D models for reports, scientific publications, and digital communication, with
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in the motivation letter. Additional optional skills and qualifications: Previous experience in: segmentation of magnetic resonance images (MRI) of the brain and spinal cord; generation of surface and
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questions related to the molecular regulation of autophagosome formation, using cell biological, genetic, and imaging-based approaches. The candidate will explore the function and regulation of proteins
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allows for studying language behaviour (time-course and quantity of gaze/eye-movements), neuro-physiology of language processing in the brain and neuro-imaging (https://www.ntnu.edu/langdevlab#/view