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knowledge of statistical methods and their application. Good knowledge of GIS and R or other statistical software is an asset. Documented proficiency in English, both spoken and written, is necessary. As the
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strong programming skills in R, Python, or equivalent. Familiarity with integrating multi-omics data, as well as applying machine learning or AI to scRNA-seq for biomarker discovery or cellular phenotype
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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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programming language (Python, R, or Matlab). Experience in medical image analysis. Excellent English communication skills, both spoken and written, as it is required in daily work. Preferred qualifications
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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
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of scientific independence is a requirement. You should have extensive experience in database management and be a skilled user of one of the common statistical programs, such as STATA or R. You should
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license (minimum Swedish license category B) is required to complete fieldwork Proficiency in statistics and experience with common statistical programming languages such as R. Scholarly profiency in oral
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or R. Experience with specialized programming languages such as GIS, MATLAB. Knowledge of policy analysis methodologies and tools. Familiarity with energy system analysis. Research Skills: Proven ability