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simulations of compact binaries (including, for example, binary black holes, binary neutron stars, and black hole–neutron star binaries). The broader goals are to generate accurate predictions for gravitational
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models. The candidate will be jointly supervised by Dr. Iris Groen (www.irisgroen.com ) and Prof. Cees Snoek (https://www.ceessnoek.info/ ). Want to know more about our organisation? Read more about
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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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will contribute to the development of a new simulation-based pre-training framework for building more robust and trustworthy machine learning-based clinical prediction models. Funded by the Medical
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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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, or predictive modelling. • Experience working with secure research environments (e.g., TREs, data enclaves). Applicants should send the following documents during the application: a. Cover letter highlighting
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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
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materials to enhance the cell robustness. Work plan The work plan for the PhD thesis will be divided in three main steps: 1) A chemo-mechanical model will be built to predict the crack initiation and
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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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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