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manipulating omics datasets, including spatial transcriptomics, RNA-seq, and single-cell RNA-seq. Familiar with high-performance computing (HPC) environment and possesses good computational biology skills
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sequence data analysis Comfort with BASH, R, and command-line usage on an HPC environments Comfort with Python3, Git, and workflow management Experience in entomological systems Point of Contact Janeen
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, as is experience of working with HPC. Excellent data organising skills, oral and written communications skills, problem-solving abilities and time management skills are also a requirement. Experience
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and MySQL databases in HPC environments for large-scale data analysis. Collaborate with interdisciplinary teams to support data-driven biological discovery. Publish scientific papers, release datasets
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or clinical datasets. Proficiency in Python and R, with strong experience in Linux/HPC environments and workflow automation. Track record of publications in high-impact journals and contributions to competitive
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postdoctoral position within the Q-VERSE EU project, which aims to provide a ready-to-use quantum software toolkit that supports various APIs and HPC interfaces in an open and transparent manner for Europe’s
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statistics. Software frameworks: Excellent programming skills in Python, R or similar, with experience in frameworks such as PyTorch, TensorFlow, JAX, etc. HPC & Big Data: Proficiency in high-performance
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Blindern, Oslo. Job description This PhD project aims to study the convergence of high-performance computing (HPC) and AI, which is a subject that sees an increasing importance due to the widespread use
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experience in working with Linux HPCs · Experience in applying machine learning methods to genomics data analysis · Experience in navigating public databases and genomics data repositories
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of large-scale genomic and transcriptomic datasets ('big data'), with hands-on experience in high-performance computing (HPC) environments (e.g., command-line interface, scripting in R/Python, use of common