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to the development of novel tools for cancer risk assessment with real potential impact on healthcare. Qualifications Requirements A doctoral degree or an equivalent foreign degree in computer science, statistics
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well as collaborate with members of the team on research projects that fit their qualifications and interests. Primarly, the selected candidate will design and implement novel ML/statistical approaches dedicated
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to different biological materials and research questions. The bioinformatic/statistic component of the proteomic pipeline is an important part of the work, to be able to assist the users in interpretation and
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pipelines for analysis of high-throughput chemical proteomics experiments, apply statistical and pathway analysis methods, and ensure that all datasets follow FAIR principles. The role includes supporting
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existing and emerging methods Support of CFG users in all aspects of data analysis and data handling Application and development of robust statistical approaches for hit calling and data interpretation
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maintain reproducible pipelines for analysis of high-throughput chemical proteomics experiments, apply statistical and pathway analysis methods, and ensure that all datasets follow FAIR principles. The role
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the lab and bioinformatic/statistical analyses of next-generation sequence data. The project will be conducted in collaboration with Prof. Göran Arnqvist (Evolutionary Biology Centre, Uppsala University
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for carrying out research in the Chinmay Dwibedi lab (www.dwibedilab.org ) in close collaboration with local and international experts. Specifically, you will employ Bioinformatic and statistical methods
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users in all aspects of data analysis and data handling Application and development of robust statistical approaches for hit calling and data interpretation Management of datasets for FAIR compliance and
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, statistical testing, and visualization to support biological discovery Solid foundation in statistical and quantitative methods Proficiency in working with Unix/Linux environments Strong communication skills