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Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial | Portugal | 29 days ago
the discrepancy between theoretical predictions and the actual observed behavior. The objective is to develop model-based artificial neural network tools that combine the strengths of traditional numerical
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processing [1–3]. The experimental results obtained will be combined with a theoretical model enabling the prediction of equipment damage and service life, with the goal of optimising their operation and
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SDLs to synthesize and characterize large quantities of candidate molecules, calibrating theoretical models with experimental data, predicting promising candidates with computational tools and machine
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, SEM, XRD, or particle size analysis Understanding of hydrometallurgical or battery recycling processes Integration of modeling or theoretical predictions with experimental work Collaborating in
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, and generate high-quality datasets for predictive microbial modelling and risk assessment. Responsibilities include contributing to the design and execution of food challenge studies, integrating
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solutions for vibration and noise control in lightweight structures (https://cordis.europa.eu/project/id/101227712 ). The project focuses on the development of Acoustic Black Hole (ABH) technologies
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ductile deformation by a dislocation creep flow law. Recent data on low-temperature dislocation dynamics predict a smaller peak resistance at the brittle-ductile transition, which favor deformation
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colleagues on multi‑omics data integration and analysis. You will also work with AI experts to help implement predictive models that improve guide design and functional genomics workflows. You will join an
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atmospheric perturbations, and improving performance under realistic operational conditions. Main activities include: • Designing and developing deep learning models to correct wavefront sensor nonlinearities
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colleagues on multi‑omics data integration and analysis. You will also work with AI experts to help implement predictive models that improve guide design and functional genomics workflows. You will join an