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, microbes will be identified that affect fermentation outcomes. Building on previous work from the host group (doi:10.1016/j.chom.2023.05.024; doi:10.1093/nar/gkaf1388), we will develop machine learning tools
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/scholarship during postdoc appointment period. Projects in the Birnbaum lab focus on plant regeneration and plant cell development. This postdoc will work on a new project on somatic embryogenesis in poplar and
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about faculty research programs, network with Fred Hutch postdocs and faculty, and learn about the postdoctoral training environment and the vast resources available at Fred Hutch. This program is
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The postdoc’s work will involve research within dynamical systems theory and network theory, with applications in mathematical modeling in neuroscience and in machine learning. In addition, a smaller amount of
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computational imaging specialist – experience in quantitative image analysis, scattering modeling, signal processing, machine learning, or neural-network-based data interpretation. The project is closely
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mathematical, statistical, and machine-learning-based analysis of complex data sets, such as hypothesis testing, supervised/unsupervised learning, linear models, etc. Experience with atlas-scale single-cell data
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and able to manage your priorities. 🎓 We are looking for people with a PhD in machine learning, deep learning, data science, computer science, obtained less than 3 years before the date of hire, with a
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Universitätsklinikum Heidelberg – UK Mannheim GmbH | Mannheim, Baden W rttemberg | Germany | 3 days ago
and machine learning methods applied to biological data Experience working with multiomics data integration is a plus Excellent organizatorial skills, strong commitment, motivation and ability to work
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the use of machine learning and AI approaches • Integration of proteomics with genetic data via MR, coloc and FUSION to identify causal and druggable targets Requirements • The successful applicant will
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fully funded PhD position in the area of safe data-driven system identification for cyber-physical systems, offered by our research group at the intersection of control theory, machine learning, and