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Field
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What you will do Perform research studies and publish in conferences and journals Supervise master’s and/or PhD students to a certain extent Possibility to engage in teaching at undergraduate/master’s
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plants in relation to their environment, of plant-related organisms and of plant production. The Laboratory of Genetics is interested in heredity in general, in particular the origin, architecture and
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | about 2 months ago
of the actuated soft-robot phantom (WP3 "PHANTOM", task T3.3), from architecture definition through experimental validation of the prototype (deliverables D3.4, D3.5). For a better knowledge of the proposed
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Max Planck Institute of Molecular Cell Biology and Genetics, Dresden | Dresden, Sachsen | Germany | 29 days ago
and organoid systems that capture key aspects of tissue architecture, cellular heterogeneity, epithelial-stromal interactions and disease-associated states (Dowbaj et al., Nature 2025; Yuan et al
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design and feedstocks, including software architecture and database, for eventual use as a new application. Lead the literature review on thermochemical conversion, biomass pyrolysis, coupled CCUS/PtX
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to work well with minimal supervision and with PhD students and external collaborators. Experience related to performance analysis and optimization, GPU architecture, and code generation are highly
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Architectures of Spontaneous versus Precipitated Opioid Withdrawal: Self-Exciting Point-Process Models of Continuous Home-Cage Behavior Across Genetically Diverse Mice. The project encompasses building behavior
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to an existing fleet-control system, while providing certified bounds on changes to closed-loop behaviour. The post holder will be a member of the Oxford Control Group and will develop new control architectures
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. The project focuses on the intersection of deep reinforcement learning, probabilistic modeling, and bio-inspired architectures (such as Spiking Neural Networks) to achieve sample- and energy-efficient robust
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optimization of large language models (LLMs) and related architectures for generative tasks, continuous learning, indexing or retrieval, support of retrieval augmented generation over many data points from long