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Details The aim of this project is to combine nanomechanical methods with modelling (i) to develop quantitative, predictive models for the behaviour of molecules in sliding contacts, and (ii) to understand
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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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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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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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al. 2019] and point-force Lagrangian models, with advanced post-processings [Vegad2024]. This work will be carried out with the YALES2 high-performance platform. Where to apply Website https
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Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial | Portugal | 27 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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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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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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, 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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, combined with a predictive operational insights model to gain superior operational performance. Employed and supported by an academic team from the University, you will be based at ELE Advanced Technologies