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, network analysis, or machine learning are a plus Good organisational skills and ability to work both independently and collaboratively Effective communication skills and an interest in contributing to a
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the use of large language models to support neural network design and data preprocessing. The position involves close collaboration with experts in cardiovascular simulation and Scientific Machine Learning
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surrogates or approximators, such as random forests or shallow neural networks, trained to mimic the outputs of the original computations at a fraction of the cost. This hybridization aims not only
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or spike correlation patterns limited to local neural circuits or span across brain regions? Set up a network model to reproduce the main results and provide potential neuronal mechanisms. Existing
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instances to solve new, yet similar, instances more efficiently than with general purpose algorithms such as Netwon`s method. In particular, we aim to develop a neural network architecture that will allow us
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Tensorflow or Pytorch is advantageous Experience in numerical methods for partial differential equations is beneficial Effective communication skills and an interest in contributing to a highly international
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will be part of a dynamic community and participate in the school’s interdisciplinary training program, including hands-on training in small groups, summer schools, networking events and hackathons
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is far beyond in-situ observational networks. However, the accuracy of satellite retrievals depends on several assumptions leading to biased observations. The aim of the PhD-project is to overcome
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Python and C++, with solid experience in scientific computing and software development; familiarity with Linux environments Excellent collaboration and communication skills and enjoyment of working in
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one programming language (Python, Matlab, R, C++, Julia, …) Good analytical skills with a sound understanding of data evaluation Knowledge of numerical simulation, for example with land surface