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Your Job: You will be a member of a consortium of leading research institutes and an industry partner. Your task is the build-up of a predictive model for tandem cell stability. Your tasks in detail
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of mold free shelf-life predictive models, determining the number of variables as well that need to be recorded to be able to train the model; (ii) design and development of a model to predict mold growth
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Sharing – Building a federated data space to enable responsible data integration and cross-project learning. AI & Modelling – Using shared data to power advanced models that help describe and predict
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complex, high dimensional and high-volume datasets. Uses data preparation, modeling and predictive modeling, analysis, processing, algorithms, and systems. Applies knowledge of statistics, machine learning
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natural and human disturbances through climate-smart forestry startegies, based on observations and predictive models. Where to apply Website https://unimol.concorsismart.it/ Requirements Additional
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programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Are you interested in the prediction and modelling of extreme flood events? Do you want to understand how
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of funding. The MLE will work on projects that will include applications of neural networks to efficacy and potency prediction for drug combinations using multimodal datasets including molecular features
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of the SU(N) Fermi-Hubbard model and its low-temperature phases at the microscopic level. Share this opening! Use the following URL: https://jobs.icfo.eu/?detail=1003
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We are a German and Portuguese start-up revolutionizing novel and high impact materials discovery using leading AI models and smart synthesis. At alqem, we believe that new breakthrough materials are a
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, and c) predicting new phenomena and discovering improved materials for applications. My efforts in this area use a variety of modeling approaches to answer questions on materials systems of interest