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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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skills are required for the job: - Computational modeling of molecular crystals. - Computational and theoretical chemistry. - Crystal structure prediction. - Familiarity with the Linux operating system
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Infrastructure? No Offer Description This project is part of the European ERC Synergy project Karst https://erc-karst.eu/ , which aims to develop a predictive flow model for an entire karst network. We will
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. Extensive knowledge of statistical methods including multivariate and univariate analysis of large data sets, learning and predictive modeling, network analysis, and probabilistic approaches to test theories
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will develop and evaluate new approaches to predicting current and future population exposure to such hazards by combining numerical modelling and remote sensing of river migration, with machine learning
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Centre National de la Recherche Scientifique (CNRS) | Saint Aubin Routot, Haute Normandie | France | 9 days ago
inverse modelling in geosciences. (https://www.ipsl.fr/ ) Task description for your Individual Research Project (IRP) Problem Definition: In order to account for the chemistry occurring in the rocket plume
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IF or CORE A*/A conference paper. Robust machine control assumes modeling of robot-environment interactions. An example may include an outdoor autonomous ground robot that needs to be aware of its
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University Work duties: This postdoctoral position is part of the AFLOW consortium supported by the Swedish Energy Agency and focuses on materials modelling of chemical stability in aqueous organic redox flow
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significant challenges for the treatment and supply of safe and high-quality drinking water. The project aims to develop a multiscale predictive analytics framework that integrates long-term algal speciation
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Quantification and spatial analysis of immune biomarkers (e.g. TILs, immune subpopulations) Development of AI pipelines for automated analysis of whole-slide images Predictive modelling of relapse and metastasis