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learning. Job responsibilities will include: Develop simulation algorithms and software to model challenging gas adsorption behavior in porous materials Develop novel machine learning model for predicting
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segmentation, tracking, classification, and more. You will utilize probabilistic models to produce uncertainty-aware predictions across scales. This role requires deep knowledge of the underlying models and
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these models for scalable vision tasks, instance segmentation, tracking, classification, and more. You will utilize probabilistic models to produce uncertainty-aware predictions across scales. This role requires
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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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variants as functional and assess their impact on gene expression. Contribute to large-scale modeling of engineered traits to predict performance and optimize design. Required Qualifications: PhD in
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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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., feature engineering, spatiotemporal modeling, Bayesian calibration, ensemble methods) to improve prediction accuracy and uncertainty quantification. Disseminate research findings through presentations
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. This includes exploring the use of digital twins for bioreactors and deploying AI driven predictive models to improve optimisation, consistency and overall yield. The main focus for this role is to work with the
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short- and long-term demand prediction, renewable generation forecasting (solar, wind, hydro) under uncertainty, spatiotemporal modeling for distributed energy systems, energy markets, transfer learning
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for our environment? Will the streets ever by quiet again? This PhD will give you the opportunity to build models that predict this! Job description In 2023, global drone shipments reached 1 million