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contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will be working primarily with
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Job Description The Section of Bioinformatics, DTU Health Tech is world leading within Immunoinformatics and Machine-Learning. Currently, we, together with Lonza Cambridge, UK, are seeking a highly
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and analysis, human-machine interaction, productivity monitoring, and proactive personalized feedback and learning methods (using augmented and/or virtual realities). We seek excellent candidates with
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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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the Danish Ministry of Foreign Affairs and managed by Danida Fellowship Council. Ethio-Nature aims to optimize the use of machine learning and remote sensing to site nature-based solutions that enhance local
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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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this date. Job description Recent improvements in machine learning have dramatically improved the accessibility of de novo protein design. In this project, we seek to exploit these developments to interrogate
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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