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Austrian Academy of Sciences, the Johann Radon Institute for Computational and Applied Mathematics (RICAM) | Austria | 3 days ago
expressivity and complexity of neural networks and neural operators, as well as on the development of novel algorithms connecting theory with practice. For more information contact Dr. Ahmed Abdeljawad
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Discovery”, with a strong scientific and environmental ambition: developing lower-footprint AI methods for real inverse problems in nondestructive evaluation. The topic has already passed the first ENACT
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of control software and data management systems for the automated laboratory. Development and deployment of AI algorithms for adaptive experimental planning, optimization of experimental space, and automated
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industry and international partners. For more details, please view https://www.ntu.edu.sg/atmri . We are looking for a Research Fellow to conduct research on air traffic management (ATM) algorithms and data
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artificial intelligence to atrial fibrillation and associated comorbidities, collaborating with Cardiology researchers to support the development and evaluation of artificial intelligence algorithms
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bioinformatics analysis pipelines for processing RNA-seq, single-cell RNA-seq, genomics and proteomics data. Develop novel algorithms and integrated data visualization applications when existing software packages
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. This includes modelling, data analysis and algorithmic development, as well as experimental validation of models and algorithms. It contributes to the performance assessment of space missions. More specifically
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and limited resources (fleet size, mobile and fixed charging infrastructure). This project aims to address these challenges by developing novel mathematical models and algorithms to support real-time
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. The ultimate goal is to develop theory and methods for the construction of low-complexity invariant sets, using computationally tractable algorithms. Funding Notes This is a self-funded research project. We
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of pinching plasmas. This research associate will work with the Michigan State University (MSU) team to develop new scalable algorithms inside of the Parthenon framework, an AMR performance portable framework