267 data "https:" "https:" "https:" "https:" "University of Michigan Ann Arbor" Postdoctoral positions in Sweden
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wider society. Chalmers was founded in 1829 and has the same motto today as it did then: Avancez – forward. URL to this page https://www.chalmers.se/en/about-chalmers/work-with-us/vacancies/?rmpage=job
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recruiting an outstanding and ambitious postdoctoral researcher in computational biology to advance the integration and modeling of large-scale microscopy data using modern machine learning approaches
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several cancer research groups represented, including joint seminars and other collaborative activities. The group uses various data sources and modern techniques to improve predictive modelling, including
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and support computational analyses of high-dimensional molecular data related to wound healing and skin biology. Responsibilities include: developing and applying reproducible pipelines for single-cell
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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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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