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Saelens team. Research Project In this research project you will develop probabilistic deep-learning models that automatically extract biological and statistical knowledge from in vivo perturbational omics
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Saelens team. Research Project In this research project you will develop probabilistic deep-learning models that automatically extract biological and statistical knowledge from in vivo perturbational omics
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continuum within the 2nd phase of CLICCS (https://www.cliccs.uni-hamburg.de/about-cliccs/cliccs-ll.html). In CLICCS-M4, we are further developing the unique ICON-Coast model within the ICON Earth System
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important modelling parameters for the digital model. Create a digital model of the wind turbine whilst having the important modelling parameters variable. Develop methodologies to solve coupled inverse
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 7 days ago
the surface properties of the Asal-Ghoubbet rift by massive inversion of the Hapke model on Pleiades multiangular images. Remote Sensing of Environment 322, 114691. https://doi.org/10.1016/j.rse
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candidates will be technically proficient in immunological techniques and provide evidence of research productivity. Prior experience with flow cytometry and in vivo mouse models is advantageous, though not
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microenvironment, and other biological processes. Conduct preclinical studies using in vivo disease models (cancer, inflammation, organ injury, etc.) and new alternative methodologies (advanced biological models
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limitations in both measurement and modelling techniques. Current in-process measurement methods are restricted to surface-only monitoring devices (e.g., cameras and pyrometers), which fail to capture
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(PICs) increasingly used in various applications. To allow a smooth design flow for these PICs, optimized compact models are needed. This PhD position is enabling compact models for optical amplifiers and
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. Currently available topics, application and more information: https://phdquantumgrenoble.univ-grenoble-alpes.fr/phd-application/available-phd-subjects PhD subjects (full list available via the attached link