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using Cell Painting and high-content imaging. Deep learning and multivariate methods, both supervised and unsupervised. Development of software and pipelines for analysis of large-scale image data
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registries and biobanks. The applicant is expected to have a strong computational focus on innovative development and application of novel data-driven methods relying on machine learning, artificial
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methods relying on machine learning, artificial intelligence, or other computational techniques. Duties The position includes research, teaching and administration. Duties includes conducting research
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application of novel data-driven methods relying on machine learning, artificial intelligence, or other computational techniques. Your tasks will include conducting independent research in the subject area at
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the national infrastructure network SciLifeLab for Cryo-EM and cellular volume imaging, providing “state of the art” technology access for this project. Cryo electron microscopy (cryo-EM) methods provide
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maintenance of instruments and computer systems, as well as assisting researchers in preparation of EM samples, data collection, and image analysis. You will also act as a coordinator for ongoing facility
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maintenance of instruments and computer systems, as well as assisting researchers in preparation of EM samples, data collection, and image analysis. You will also act as a coordinator for ongoing facility
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and/or functional imaging or application of computational modeling, machine learning and AI to understand cellular function. At least five years’ experience working within the university system, another
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focused on mass spectrometry and development of new techniques for mass spectrometry imaging and single cell mass spectrometry to reveal chemical processes of importance to biological function and
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of the proteins involved in the project, but also applying machine learning to predict the effects of allosteric modulation and to understand the biology of the specific systems we are studying. Qualification