582 machine-learning-"https:"-"https:"-"https:"-"https:"-"RAEGE-Az" positions at Nature Careers
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or other large-scale biological data), using statistical methods, pathway/network analysis or machine learning. The candidate will conduct integrative analyses of biomedical datasets, focusing on single-cell
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. Antonio Scialdone’s group at Helmholtz Munich, a leading European hub for AI in biology. The successful candidate will design and implement physics-informed machine learning frameworks and predictive models
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hypotheses. Develop, refine, and benchmark computational pipelines using statistical modeling, machine learning, and deep learning approaches. Conduct analytical validation studies including precision
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computational pipelines for multiplex imaging, spatial transcriptomics, single cell RNAseq, and multi-omics data integration. Lead graph-based network and machine learning analyses of tumor immune
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for experimentation, yet they remain difficult to deploy directly onboard robots due to hardware availability, latency, sampling cost, and noise. Previous work on quantum machine learning (QML) emphasize
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, including approaches that produce “black box” data that might only be actionable in conjunction with AI and machine learning methods. Experimental technologies could cover (but are not limited to) single-cell
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with experts to automate diagnostic assays, leading to cost-effective, easy to use tests Work closely with AMR, Informatic and Machine Learning colleagues ensure the tests provide accurate pathogen ID
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programme at the Faculty of Science . The ideal candidate has a background in or experience with one or more of the following topics: Advanced deep learning architectures Mathematical foundations of machine
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funding and lead research projects, conduct innovative data-driven research in life sciences using computational modelling, machine learning and advanced analytics, publish in high-impact international
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informatics, molecular simulation, computer-aided molecular design, and chemically aware machine learning. Our mission is to enable a deeper interrogation of biology through the integration of chemistry