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theoretical methods and algorithms are required. The research project aims at deriving priors for Bayesian methods from atomistic simulations and machine learning. It also offers the opportunity to work with
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challenging, and new theoretical methods and algorithms are required. The research project aims at deriving priors for Bayesian methods from atomistic simulations and machine learning. It also offers
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sampling algorithms to Bayesian learning paradigm Quantum-assisted training algorithms for sparse machine learning models. What you bring to the table Formal conditions to start a master thesis on a German
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of study Good Java and/or Python programming skills Machine learning knowledge and experience Experience with Static Analysis is recommended Good language skills in German and/or English What you can expect A
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, are all essential advancements to enable a wider and more secure deployment of the technology. Most biometric systems are based on image analyses. Therefore, exciting challenges in the computer vision
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on machine learning methods. The methods for this will be comprehensively further developed. You are interested in the design and training of neural networks and machine learning methods in general? We can
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-jamming machine learning and digital twinning applications in industry and medicine Transmission and signal processing techniques for joint communication and sensing, including waveform and frame design
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movement by high-resolution fluorescence microscopy and/or magnetic/optical tweezers, (iv) quantitative image processing, data analysis and modeling. The project is funded by the MARIE SKŁODOWSKA CURIE
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movement by high-resolution fluorescence microscopy and/or magnetic/optical tweezers, (iv) quantitative image processing, data analysis and modeling. The project is funded by the MARIE SKŁODOWSKA CURIE
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and evaluation of innovative data- and machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization methods