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methods are developed in parallel, the postdoc will develop systems and services that make biological data accessible to AI and computational tools, collaborating closely with the Human Protein Atlas (HPA
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association study (GWAS) summary statistics. Analyze single-cell and bulk genomics datasets using standard and custom bioinformatics pipelines. Contribute to grant writing, manuscript preparation, and
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) Bioinformatics and Statistics, and (3) Data Science Methods. The postdoc will be part of the Data Science Methods group, which has a strong research focus on privacy-preserving techniques. CLINDA includes 17 core
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knowledge for a better world. You can find more information about working at NTNU and the application process here. About the Job We have a vacancy for a full-time three year researcher at the Department
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innovative high-throughput sequencing technologies, bioinformatics approaches, and multi-scale models to elucidate RNA-mediated endothelial biology in the context of diabetes. In parallel, the lab emphasizes
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to create knowledge for a better world. You can find more information about working at NTNU and the application process here . About the position Are you ready to take your research career to the next level
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process here . ... (Video unable to load from YouTube. Accept cookie and refresh page to watch video, or click here to open video) About the position Are you ready to take your research career to the next
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, enhanced sampling, QM/MM) Experience improving performance and scalability of simulation workflows via: Parallelization and performance engineering GPU/accelerator optimization Algorithmic innovation
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/or cells) for MS-based metabolomics and lipidomics. You have experience in bioinformatics to process HRMS data for statistical analyses and biomarker discovery. Your research qualities are in line with
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Description Primary Duties & Responsibilities: Implements: Algorithms and computer software for analyzing omics-based data sets [high-throughput, massively parallel genomic/proteomic/clinical]; Data management