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appropriate statistical testing to test the efficacy of the models. The project forms part of a wider effort for developing an effective VR HRI toolkit for improving interactive fluidity between robots and
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spatial verbs will be systematically tested in the comprehension and production of Italian sign language, in order to trace for the first time how spatial language changes across the lifespan. Data will
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focused on elucidating molecular and cellular pathways underlying photoreceptor degeneration and testing therapeutic interventions in relevant disease models. This position offers opportunities to work in a
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their system-level integration Develop design architecture and break down requirements into functional blocks Create and execute test benches for RTL and timing simulations Create design documentation in
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fields) controls comb bandwidth, stability, and tunability. Test predictions in mid-infrared quantum cascade lasers, with direct feedback between modeling and experiment. Profile Background in physics
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robust and fast HSI-based detection method using deep learning (CNNs and pixel-wise classification). • Creating a comprehensive dataset of hyperspectral images for training and testing models
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relevant discipline such as mechanical engineering or physics. Experience in laboratory testing or numerical modelling is desirable. Excellent written, oral communication skills, and competence in
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colorimetry Development of molecular assays for the detection of multiple targets simultaneously Adaptation of molecular assays for point-of-care (PoC) testing Impact: The PhD project will contribute
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are enabling new applications ranging from fundamental tests of physics to relativistic geodesy and improved timekeeping. However, their performance is presently limited by the need for ultra-stable reference
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of the recruitment and selection by the funding authority) - Type of competition tests: Analysis of the competition file (eliminatory) - Interview The competition will be organised as follows: - submission