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About the German Cancer Research Center (DKFZ) The German Cancer Research Center (Deutsches Krebsforschungszentrum, DKFZ) is Germany’s largest biomedical research institute and a member of the Helmholtz Association of German Research Centers . Over 3,200 staff members from 88 nations are...
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of snapshots taken with high-throughput super-resolution microscopy and are looking for a Postdoctoral Researcher with a background in machine learning. About the position/ the research project The overall aim
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of protective responses for infectious diseases, particularly COVID-19 and influenza. The role involves the application of state-of-the-art software development methods, machine learning, and AI techniques
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electron microscopes, nuclear magnetic resonance machines and other imaging instruments, a class 100 cleanroom for nanofabrication, a series of research vessels to explore the Red Sea, and much more. They
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. UKF jobticket UKF Your challenges: develop and optimize high-throughput analysis pipelines integrate complex RNAseq, Whole Exome Sequencing and TCR repertoire high-throughput data apply machine learning
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of protective responses for infectious diseases, particularly COVID-19 and influenza. The role involves the application of state-of-the-art software development methods, machine learning, and AI techniques
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Postdoc in CRISPR Meta-Analytics and AI for Therapeutic Target Discovery and Priotisation (OT Grant)
solutions. Situated in the Computational Biology Research Centre of HT, the Iorio Lab operates at the intersection of biology, machine learning, statistics, and information theory. Our goal is to comprehend
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to application of machine learning and data mining techniques to analyze multiple data modalities related to corneal disease, including imaging, genetic and clinical data. Qualifications PhD in Computer Science
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of the second year after a trainee joins the team. Job Duties Designs and implements novel computational algorithms for data analysis, feature extraction, and predictive modeling. Applies machine learning
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approaches such as transcriptomics, proteomics, CyTOF and metabolomics. Developing cloud computational infrastructure, integrating multi-omics datasets and applying machine learning methods to high dimensional