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modelling photonic devices and physical reservoir computing systems. The activities within the project will benefit from synergies with other projects in the group as well as with other activities
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water quality parameters and predict cyanobacteria blooms in the Tietê system reservoirs. Activities: 1. Develop machine learning models for estimating water quality parameters via remote sensing; 2
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the flexibility and power of NNs with the ability of LMMs to robustly learn from structured and noisy (non i.i.d.) data, applying them on the prediction of both plants and human phenotypes. These models will
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related topic and need to have expertise in working with data from the National Drug Treatment Monitoring System (NDTMS), working with government and expertise in quantitative prediction modelling
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types will change under different climate change scenarios based climate projections. This framework will be ultimately included in a flood prediction model, which will be developed within the VIDI
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monitoring. • Develop numerical models to simulate the dynamic behavior of mooring and anchoring systems under different environmental conditions. • Analyze and optimize structural performance and predictive
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) for predictive modeling. Collaborate with neuroscientists, biostatisticians, and clinical researchers within BBRC and external partners. Contribute to manuscript preparation, presentations, and dissemination
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? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Development of advanced CFD models in OpenFOAM for the simulation of next
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, the Engineer will architect, engineer, and deploy AI pipelines that push technological boundaries for our clients. The Engineer will tackle complex challenges at the intersection of Large Language Models
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and observation models to reflect real-time changes in environmental conditions, enabling more accurate predictions of adaptation impacts and thereby supporting a better-informed, resilient decision