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experience working with spatial data. Experience meteorological and pollutant transport models. Familiarity with measurement methods in atmospheric sciences (e.g. lidar, particle counters) A valid category B
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. You will explore how emerging AI technologies—foundation models, generative design tools, agent platforms, reasoning engines, and reinforcement learning—can be adapted and extended for maritime design
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Pytorch and/or JAX deep learning models. Experience in single-cell or spatial omics data analysis. What we offer Embedding within a computational team, with extensive experience in computational biology and
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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
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tissue using genetic mouse models, functional screens, and single cell and spatial omics technologies. More details about the laboratory: https://www.ibt.cas.cz/en/research-laboratories/laboratory
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exposures and human health, e.g. distributed lag nonlinear models, spatial Bayesian methods, case time series, case crossover; have experience with the management and analysis of large climate and/or health
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and conduct complex in vivo and ex vivo experiments focused on fibroblast biology, ECM remodeling, and tissue mechanics using advanced mouse models. Apply histological, imaging, and molecular approaches
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group Physical Geography, which has a sound reputation in the research domains of landslides, “human impact” on geosystems and spatial modeling of geomorphic processes as well as in the applied research
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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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, the individual will: 1) Analyze acoustic data with existing software (Echoview, R, Python). 2) Collaborate with USGS scientists on field data collections. 3) Investigate the spatial patterns of fish and