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Computational modeling of metal alloys using an Integrated Computational Materials Engineering (ICME) approach. Responsibilities: 60% Perform research on the microstructural evolution of metal alloys during
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computing. This particular position focuses on time-series analysis and forecasting using transformer based foundation models. About the Project Time-series prediction using transformer based models is
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by Renew Risk Ltd. (https://www.renew-risk.com/ ), offering opportunities to work with real offshore wind farm models and industrial datasets while addressing real-world challenges in collaboration
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+ animal models), therefore the winner will have to carry out activities in at least three key areas: in vivo experimentation, Alzheimer's (AD) biomarkers, and bioanalytical detection technologies
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applications. Key Responsibilities: Develop and fine-tune computer-vision models, instance segmentation, and retrieval-based estimation from images and text metadata. Build and evaluate monocular depth pipelines
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proceed with the definitionand numerical implementation of the models for the simulation of the magnetic, electrical, thermal, and mechanical behavior of these devices. Appropriate experimental setups will
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review of fire modeling. Improvement of selected models. Analysis of the implications for transport networks. Where to apply Website https://sede.uvigo.gal/public/catalog-detail/28364578 Requirements
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Job Purpose To make a leading contribution to the BIOGRAPH – Biophysical Tumour Growth Modelling for Novel GBM Treatment Response Assessment: Harnessing Physics-Informed Deep Learning project
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in cancers of unknown primary (CUP). Your Role You will join Subproject 3 (Model Alignment and Optimization), led by PD Dr. Keno Bressem (https://scholar.google.com/citations?user=wIEgwbkAAAAJ&hl=en
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protein structural insight with hands‑on ML development: adapting and applying state‑of‑the‑art structure prediction and design frameworks, training/fine‑tuning models, and running scalable computational