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/researchers, and we work with amazing partners, including other Harvard Medical School-affiliated hospitals. Focus: Develop next-generation computational systems for biomedical and clinical data using
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for tumor behavior and clinical outcomes Development and implementation of artificial intelligence and machine learning algorithms for biologically and clinically motivated questions in pediatric oncology
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Research Center for Molecular Medicine (CeMM), ÖAW | Graz 12 Bez Andritz, Steiermark | Austria | 3 months ago
; and how these mechanisms can be understood, modelled and ultimately perturbed for biomedical discovery. Two scientific tracks Track 1: Computational Biology / Machine Learning for membrane protein
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Institutions. Preference factors: Previous experience in biomedical image and signal processing; Previous experience in computer vision; Minimum requirements: Degree in Computer Science, Informatics Engineering
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Oden Institute for Computational Engineering and Sciences | Austin, Texas | United States | 2 months ago
genetic data Multimodal machine learning for biological discovery Translational genomics and risk modeling The fellow will work in an environment that emphasizes methodological innovation, statistical rigor
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of metabolism, membrane transport, cellular regulation, structural systems biology, machine learning and disease mechanisms. These positions are embedded in the transition from CeMM in Vienna to the newly founded
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but not limited to the following: Develop new computational tools through the application of AI / deep learning / machine learning / statistics on spatial and single-cell omics (transcriptomics
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these activities. Other laboratory responsibilities, as they arise, under the direction of the PI. Required Qualifications* MD or PhD degree in biomedical sciences (or related field) with a minimum of 3 years
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, including parsing and processing large document corpora. Strong understanding of machine learning or AI methods applied to health or biomedical data. Demonstrated ability to assess model outputs, identify
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possible renewals, a cumulative period of four years of research fellowship intended for doctoral students. Preferential factors: Research experience in the areas of Bioinformatics and Machine Learning