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learning and physics, addressing key challenges in modern quantitative biology. The successful candidate will be responsible for: • Develop and train deep learning models (CNNs, ...) data to predict IPLSs
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missions operated by LATMOS. The postdoc will employ deep learning approaches using satellite data and ground stations. -Understanding the infrared data from the IASI mission and identifying the channels
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on developing deep learning methods for the reconstruction and physical analysis of ATLAS experiment data. The selected candidate will develop innovative analysis methods for the reconstruction and physical
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on deep learning coupled with molecular simulations for the investigation of slow variables and transition pathways describing large conformational changes and reactive processes in complex biological
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mediation produce, or fail to produce, a deep and distanced historical understanding. The central challenge is to understand how certain configurations of the design space support an active construction