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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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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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. 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 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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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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into the cancer genome and epigenome using long-read sequencing and machine learning Gaining novel insights into the cancer genome and epigenome. This project will generate and analyse nanopore long-read sequencing
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Climate Science, Hydrology, Environmental Science, or a related field. Experience in machine learning or AI applications in hydro-climate studies. Strong background with GIS tools and spatial analysis
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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
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Nature Careers | Vancouver South Shaughnessy NW Oakridge NE Kerrisdale SE Arbutus Ridge, British Columbia | Canada | 8 days ago
well as healthy older people. You will be using generative machine learning models, which may include different approaches of generative deep learning (e.g., generative adversarial networks and diffusion-based
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in the application of machine learning methods, mixed models, clustering techniques, sinusoidal regression, and regression splines. Medical background and knowledge of biochemical processes is a plus