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. The PhD (M/F), to be recruited in the context of the ERC StG MULTI-viewCELL, will be working on the development of a new method combining machine learning and biophysical modelling to model embryo
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material platforms exhibiting time-varying responses. Using adjoint-based optimization and spatial structuring, to realize complex time-modulated medium dynamics with realistic material constraints and
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Neuroscience, or a related field—or an equivalent combination of education and relevant experience. 3+ years of experience fine-tuning spatial transformer networks, contrastive learning, model distillation, RLHF
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. This data will be used as input in climate models to ultimately propose a spatial characterization of bike paths. The methodology will be tested in several areas in France and Switzerland and discussed with
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collaborative research environment to analyze unique spatial data in an innovative manner. You will develop and perform cutting-edge bioinformatic analysis integrating different multiplexed spatial data, and gain
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-scale atmospheric conditions. Most current regional and global atmospheric chemistry models struggle to represent plume processes. Their spatial resolutions are typically too coarse to resolve plume-scale
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bright points to solar jets, called spicules. The study will involve mathematical modelling complemented with observational data analysis using high spatial, temporal and spectral resolution solar
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, the candidate will work in an interdisciplinary team of biologists, statisticians and philosophers, including one other PhD student (statistics) and two postdocs (spatial forest ecology and philosophy/social
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interested in mammalian stem cell biology, reproduction, and development. They use cutting-edge single-cell, spatial, in vitro, and surgical approaches in multiple model species and in human organoids
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propagation in spatially periodic, non-dissipative media, such as electromagnetic, elastic, or acoustic waves in metamaterials. This decomposition can also be applied to analyse the growth or decay of flow