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. This may involve techniques such as spatio-temporal regularization, discrete tomography, low-dimensional latent representations and machine learning. The ultimate aim is to reduce the carbon footprint
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forecasting. You will get the opportunity to participate and influence the development of advanced forecast solutions combining weather forecasts and novel machine learning/statistical forecasting methods
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Job Description Are you a cybersecurity researcher eager to push the boundaries of cyber-deception? Do you have expertise in cybersecurity, machine learning and/or cyber-psychology? This fully
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and proposal preparation. Required qualifications: As a formal qualification, you must hold a PhD degree (or equivalent) in computer science, computer engineering, networking, or related fields relevant
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spatio-temporal regularization, discrete tomography, low-dimensional latent representations and machine learning. The ultimate aim is to reduce the carbon footprint for the construction industry and enable
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. Postdocs will be supported in improving their CVs for academic careers. This includes co-supervision of MSc and PhD students, teaching opportunities, and proposal development. You can learn more about ESE
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of machine learning, remote sensing and hydrology to evaluate and validate nature-based solutions that enhance local recharge and support the replenishment of shallow groundwater systems in dryland
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extraction) that can be miniaturized and integrated into portable devices. Perform SERS measurements and data analysis of SERS data (e.g., using machine learning). Develop, test and apply new fiber-based SERS