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opportunity as an Industrial PhD student to work on a project that applies machine learning to improve diagnostic and reporting workflow processes in clinical kidney pathology. This project is a collaboration
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A PhD student position in computational microbial ecology is available at the Department of forest mycology and plant pathology , Swedish University of Agricultural Sciences in Uppsala
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, high-throughput imaging of biological specimens, and large-scale remote monitoring of organisms or habitats. The PhD project in computational microbial ecology will utilize a data-driven approach to
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, including around 45 PhD students, work at the department. New employees and students are recruited from all over the world and English is the main working language. The department is located at the Biomedical
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(radiomic) data analysis. The PhD student will implement an AI-based pipeline to extract various metrics from brain magnetic resonance images. This will involve a research visit to the Resilient Brain Lab
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components from major off-the shelf providers like Thorlabs/Newport Experience with multi-photon microscopy or other non-linear optical techniques Experience in image processing and analysis with ImageJ/Fiji
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gathers a unique combination of expertise in computerized image processing, human computer interaction, and computing education. SciLifeLab BIIF is administratively placed here, and offers education and
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possess a Master’s degree in Computer Science and Engineering, or a closely related field such as signal processing, machine learning, statistics, or bioinformatics. Expertise in image analysis and deep
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group Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular processes
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precision medicine is expected to use existing strong assets in Sweden and abroad, such as molecular data (e.g. omics), imaging techniques, electronic healthcare data, longitudinal patient and population