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of teams and programmes of significant size in terms of budget and human resources preferably in an international context A well-established network and a deep understanding of challenges and opportunities
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& Research Learning about danger: a virtual reality approach to study learned predator recognition in fishes Yanell Braumuller PhD candidate Leiden University & Naturalis Biodiversity Center Rooting for
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and behavioural speech features. Integrate neuroimaging, speech and clinical data using multivariate and machine-learning approaches (e.g. UMAP). Investigate the effects of deep brain stimulation
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Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Join an ambitious deep-tech venture backed by the European
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infrastructures, rapid innovation cycles, and even autonomous deep space exploration. As Head of the In-Orbit Technology Demonstration Division, you will be at the heart of this transformation. You will lead ESA’s
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, or related background. Strong background in machine learning, computer vision, and deep learning. Knowledge of transformer architectures and foundation models. Experience with few-shot learning, self
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the next generation of managers as they investigate the opportunities presented by data analytics (machine learning, deep learning, data mining) and new information technologies (platforms, cloud computing
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machine-learning approaches (e.g. UMAP). Investigate the effects of deep brain stimulation on speech production in relation to individual connectivity profiles. Coordinate closely with clinical
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research profile, and an international network around big data in marine sciences. The candidate will have access to NIOZ’s high-performance computing cluster, GPU nodes for deep learning, dedicated data
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: Roadmapping optical technology developments and the introduction of new capabilities for space missions, from low to high technology readiness levels; Introducing deep-space optical communication into space