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Brandenburg University of Technology Cottbus-Senftenberg • | Cottbus, Brandenburg | Germany | 1 day ago
job fair and online recruiting event to connect students with employers FIT@BTU: a DAAD-funded project that helps students make the transition to a successful career Start up your Career in Brandenburg
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of machine learning algorithms are of real interest in improving the accuracy of water quality measurements, particularly in identifying, accounting for, and neutralizing ionic interference. The second key
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to have good knowledge of computer science, mathematics, algorithms, and programming. Knowledge and experience in artificial intelligence and machine learning is expected, but not required. Knowledge and
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, Edge, IoT)• Scheduling and optimization algorithms• Data streams, data management and data pipelines• software engineeringExpert programmer• Java• at least one other programming languagePractical
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; they make sense to humans and are accessible to algorithmic techniques while neural models are adaptive and learnable. The aim of this project is to develop models which combine these advantages. The project
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Description The majority of hydrological models rely heavily on the principle of mass balance, often represented through Ordinary Differential Equations (ODEs). These models encapsulate the conservation of mass within hydrological systems, ensuring that the inflows, outflows, and storage changes...
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, algorithms, and programming. Knowledge and experience in artificial intelligence and machine learning is expected, but not required. Knowledge and experience in deep learning and generative AI is considered
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The Medicines And Healthcare Products Regulatory Agency; | Canary Wharf, England | United Kingdom | about 1 month ago
of CPRD's interventional research services. Responsibilities include defining the strategy and implementing standard methods and algorithmic approaches to data capture, transformation and export; undertaking
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reference architecture for data visiting. This paradigm enables algorithms to securely access and process data within the environments where it resides, supporting federated learning for training machine
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-world error patterns: we therefore aim to go beyond the traditional depolarizing error model generally accepted in the quantum coding community. One therefore wishes to adapt existing decoding algorithms