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Field
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Responsibilities: To independently undertake research on data-efficient object detection with key techniques in few-shot learning, transfer learning, image synthesis, etc. To produce research reports and/or
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complete Data management for the project including data collection, cleaning, coding, analysis and interpretation of primary/secondary datasets using statistical software packages collaborate and build a
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Instituto de Investigação e Inovação em Saúde da Universidade do Porto (i3S) | Portugal | 8 days ago
the recording of dendritic electrical signals using electrophysiological and imaging techniques. The fellow will be involved in setting the protocol for imaging voltage signals in dendrites of pyramidal
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of building secure, reproducible workflows that make this process seamless for researchers and clinicians. You’ll also have a flair for coding in python and/or Laravel, problem-solving, with experience in web
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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research projects focused on brain connectivity. Conduct quantitative brain imaging analyses. Keep up-to-date on the literature in this field, methodologies and software analyses programs Foster research
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executive functions, including decision-making, attention and predictive coding. Key responsibilities will include: Research: Undertake human testing, conduct analyses of behavioural and brain imaging data
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biomedical image and signal processing; Previous experience in computer vision; Minimum requirements: Degree in Computer Science, Informatics Engineering, Data Science, Bioengineering or Applied Mathematics
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prototype, analysing metrics of energy consumption, range and user comfort in order to quantify the gains over conventional controllers. Objectives: 1. Investigate existing solutions and identify
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of high-affinity antibodies without triggering autoimmunity. To address this, our research program heavily focuses on studying T and B cell population dynamics through intravital 2-photon imaging and the