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developing models that predict the effects of variants. We tackle this challenge via two main directions: (1) developing efficient pangenomic data structures and evolutionary models, and (2) designing deep
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main goal, based on detailed studies of Earth and the solar system, is developing predictive models to identify habitable planets around other stars. Within three different research themes: (1) Planets
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topics: a) introduction of highly efficient DGL models to reduce the energy impact and increase the sustainability of DGL models; b) increase the expressiveness of DGL models, obtaining better predictive
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attention to scientific rigor and interpretability Experience with XAI tools (SHAP, LIME, Integrated Gradients) to identify which features of the model are driving the predictions Clear written and verbal
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through in vitro cell models. 2. Workplace The workplace is located at the Porto facilities of Universidade Católica Portuguesa. 3. Remuneration Gross monthly pay is 1402,88€, plus meal allowance, to which
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analytical approaches and technological tools (e.g., artificial intelligence, remote sensing, environmental informatics, predictive modeling, and/or environmental genomics). Research should address pressing
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Research Infrastructure? No Offer Description Mission: Support the design, training and validation of temporal models aimed at detecting ecological patterns and predicting events such as the bloom of Oceanic
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strategic raw material (CRM) deposits within Paleoproterozoic cover sequences that overlie an Archaean basement. Existing structural models for the cover rocks predict that crustal-scale fault and shear zone
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of the fluids under consideration. This will be coupled with the use of in-house models that can be employed to explore and predict the behaviour of newly developed fluids in different components and applications
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Overall, Purpose of the Job The main tasks are to advance the use of high-fidelity modelling to improve understanding of the characteristics of the turbulent wakes that develop downstream of large