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of projects could also be included. Work can include, but is not limited to, development of pipelines in Nextflow or Snakemake, scripting in Python and/or R, and running large-scale analyses efficiently in HPC
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competitive level Proficiency in a scripting language like R or Python, as well as ability to work efficiently in a Linux command-line environment and on high performance computer clusters Excellent
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previous experience of the Spatial Transcriptomics method and data analysis as well as knowledge of the programming language R. The PhD student will be at KTH, Department of Gene Technology, SciLifeLab
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or development connected to infection biology, immunology or epidemiology Advanced integration of multiple layers of molecular data sets Programming knowledge in R and/or other programming languages
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neoantigen targeting. Substantial experience working in bash scripting and HPC Linux/Unix environment. Proficiency in programming (preferably Python, SQL, groovy, R, html, JavaScript, and bash). Good knowledge
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strong publication record in relevant fields Proficiency in programming (e.g., R, Python, Bash) Effective communication in English is required for daily work. After the qualification requirements, great
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initiative and multitasking ability. Bring experience in interdisciplinary research fields. Show a solid research background in cancer biology. Be proficient in Bash, R, and/or Python. Communicate effectively
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and/or transcriptomics data Practical experience of working in Python and/or R, and Git Practical experience of working in computational cluster environments Knowledge of tumor and immune biomarkers
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or R are required (Python is preferred). Experience with analysis and visualization of large data is expected. Fluency in written and spoken English is required. Merits: Proven ability to write