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technologies. The target chips include digital signal processors, radio frequency and millimeter wave frontends, data converters, as well as larger systems with a mixture of analog and digital signals. Our
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visual methods. By combining a global mapping of key actors, data flows, carbon credits, and financial transactions with in-depth case studies and insights from farmers themselves, the project will provide
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will also use focussed ion beam milling scanning electron microscopy (FIB-SEM) to prepare infected cells for in situ cryo-ET. The resulting tomographic data will be analysed by machine-learning assisted
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university. More information about us, please visit: the Department of Biochemistry and Biophysics . Main responsibilities The Pollak Dorocic lab at Stockholm University studies the diversity
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cohorts. Within these studies, detailed dietary data are combined with sustainability indicators to investigate associations, as well as potential synergies and trade-offs between dietary health effects and
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biology, analytical chemistry, evolution, and data science. The workplace offers access to state-of-the-art core facilities for advanced microscopy and cytometry, cell and molecular biology, extracellular
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anaerobic culturing techniques (e.g. anaerobic chamber, bioreactor) and analysis of 16S sequencing data. Furthermore, practical experience in working with mouse models is required. Other requirements
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in radiotherapy with the goal of enabling fully adaptive radiotherapy. The work is based on deep learning, where models are trained on generated or clinical data. The project is carried out in
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). The project focuses on developing computational models for cancer risk assessment, integrating multiple types of data and risk factors. The main objective is to design and apply machine learning and deep
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includes a combination of experimental work, data analysis, as well as interpretation and presentation of research results. The main part of the work for the advertised position involves studies of specific