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Field
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Proficiency in standard software (e.g. text processing, statistics) and skills in handling, processing and analysis of large datasets or the interest in acquiring these skills. Strong scientific writing and
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experience with methods of molecular biology and/or in the field of histology Experience in animal experimentation is an advantage Knowledge of statistical methods for data analysis Very good written and
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international applicants from low- and middle-income countries (LMICs) with excellent grades and a strong scientific background and interest in biometry, statistics, epidemiology, public health or similar fields
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) for simplified data storage and submission Collaboration on tool development for multi-omics data integration (genomics, transcriptomics, proteomics, metabolomics, lipidomics), statistical evaluation and
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and methodological skills with a focus on quantitative data analysis (e.g., econometrics, statistics, machine learning) a high motivation and the ability to work independently with a strong team
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position. Requirements: outstanding university degree (typically M. Sc.) in Computer Science, Data Science, Statistics, Mathematics or another relevant field study with good GPA (at least finished before
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user experience and learning effectiveness Contributing to research activities relevant to ASSURED, e.g., conference and journal papers on topics such as data governance, privacy and statistical
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on the topic assigned for each position. Requirements: outstanding university degree (typically M. Sc.) in Computer Science, Data Science, Statistics, Mathematics or another relevant field study with good GPA
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development for multi-omics data integration (genomics, transcriptomics, proteomics, metabolomics, lipidomics), statistical evaluation and visualization in the Lipidomics Informatics for Life Science network in
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periods, helping to troubleshoot on-the-ground challenges, conducting statistical data analysis and visualizing results, writing and submitting research papers, presenting your research at academic