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/bayesian/deep-learning analyses, with functional validation in spruce via CRISPR-Cas9 and nanoparticle delivery. The postdoc will join Professor Nathaniel R. Street’s team at UPSC, working closely with
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. The primary objective is to develop computational methods, using deep learning–based protein design, for the successful design of 2D lattices. These methods will then be applied to generate designs targeted
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risk factors. The main objective is to design and apply machine learning and deep learning methods to understand and investigate the functional behavior of gender-specific cancers. The work will include
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related to staff position within a Research Infrastructure? No Offer Description Description of the workplace Automatic Control is an exciting and broad subject, covering both deep mathematics and hands
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postdoctoral position under the introduction of Kathlén Kohn . The position focuses on research in the intersection of algebraic geometry and deep learning or computer vision. The position is financed by Kathlén
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: https://ki.se/en/cmb/enric-llorens-group Duties We are seeking a talented and enthusiastic postdoctoral fellow to apply cutting-edge single-cell and spatial genomics approaches in combination with
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these postdoctoral positions are aimed for you! Subject description We are hiring 1-3 postdocs within the following projects: The first project, Dual Control at Scale: Learning-based control for systems
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work with deep learning frameworks (e.g., pyTorch, TensorFlow) Proven publication record in relevant fields Familiarity with high-performance computing environments Familiarity with using and adapting
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learning, and responsible AI. More info about the research groups: https://www.umu.se/en/department-of-computing-science/research/research-groups/ . Qualifications To be appointed under the postdoctoral
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Intelligence group and the Deep Data Mining group at the Department of Computing Science, collaborating with researchers in, e.g., data science, machine learning, and responsible AI. More info about the research