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Field
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fellowship in the amount of R$ 12,570.00 monthly and a research contingency fund, equivalent to 10% of the annual value of the fellowship which should be spent on items directly related to the research
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@bicmr.pku.edu.cn Tel/Fax: +86-10-6274 4134 Beijing International Center for Mathematical Research Peking University, Beijing 100871 P. R. China Application Materials Required: Submit the following items online
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of the project is to develop modular, interoperable R packages that can be integrated with new user-friendly visual data processing applications for metabolomics data analyses in life-sciences, which can be used
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Veterinärmedizinische Universität Wien (University of Veterinary Medicine Vienna) | Austria | 5 days ago
contributions, technical reports, or other scientific outputs • Documented experience in the ecological aspects of hibernation research • Demonstrated proficiency in the programming language R or advanced
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of a programme of R&D projects aimed at the development and implementation of advanced systems of cybersecurity, artificial intelligence and data science in public administration, as well as a scientific
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communication skills Preferred Qualifications: Experience with neurorehabilitation or motor recovery research Proficiency in programming and data analysis tools (e.g., MATLAB, Python, R, SPM, FSL) Familiarity
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Project. The selected candidate will receive a FAPESP Postdoctoral Fellowship (R$ 12,570.00 per month) plus a Technical Reserve equivalent to 15% of the annual fellowship value, designated for research
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-de-selecao-pos-doutorado-fapesp/ The position is open to Brazilians and foreigners. The selected candidate will receive a FAPESP Postdoctoral Fellowship in the amount of R$ 12,570.00 per month and a
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LevelPhD or equivalent Research FieldComputer scienceEducation LevelPhD or equivalent Skills/Qualifications PhD in ecological, marine or computer science with skills in python and/or R, QGIS, database and
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Responsibilities: · Develop novel statistical methods for robust pathway analsysis · Develop novel statistical methods for spatial transcriptomics data analysis · Data management · R