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formulating constitutive and damage laws that capture cavitation-driven processes, implementing and verifying robust large deformation solvers, and performing rigorous verification and validation using datasets
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micrometeorology, greenhouse gas exchange, tree and/or ecosystem physiology Relevant research experience can be based on observations, modelling or statistical analyses Excellent command of large data analyses as
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description You will support the TreeAI global initiative by developing data driven methods to enhance large scale tree monitoring. The role focuses on managing and expanding the TreeAI database and advancing
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can we use Foundation Models, VLMs, VLAs, and robot learning for complex and long-horizon tasks that involve manipulation, locomotion, and navigation in potentially unstructured and large-scale
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, ample lab space and technical support, and a rich scientific environment with a large and active community. This position is available upon agreement and is in the lab of Prof I. Mansuy, Laboratory
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-cell data) using existing pipelines Demonstrated ability to enhance, optimize, and extend existing computational pipelines, as well as design and implement new workflows Experience working with large and
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frames). Project background The work focuses on data-driven generation of structural systems. You will be involved in developing, experimenting with, and evaluating machine learning models that help
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data collectedfromtwo cattle breeds. Existing PacBio HiFi sequencing data will be complemented with ultra-long sequencing using ONT to build near complete assemblies for the sex chromosomes. This sub
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occur frequently near mountain ranges and have particularly large climate change trends there. The combined effects of mountains and climate change on thunderstorms are poorly understood, as modeling
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cutting-edge technologies to dissect these interactions: high-density microelectrode arrays (HD-MEAs) for large-scale electrophysiology, spatial transcriptomic methods, and human iPSC-derived neuronal