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and show strong quantitative skills, proficiency in coding (e.g. Python or MATLAB), and experience handling large datasets. Knowledge in at least one of the following is essential: ocean interior
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. Multiple postdoctoral fellow positions are initially available, and candidates are strongly encouraged to review Preferred Qualifications to determine which position is best aligned with their skills and
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well as to provide a strong foundation for further research projects. Each position term is subject to performance as well as research program needs and funding. Multiple postdoctoral fellow positions are initially
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resourceful, organised, and able to manage multiple priorities effectively. e) Be highly numerate, analytical, and be willing to work with complex datasets. The ideal applicant should also: a) Have experience
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well as to provide a strong foundation for further research projects. Each position term is subject to performance as well as research program needs and funding. Multiple postdoctoral fellow positions are initially
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the appropriate area. Familiarity with statistical analysis software (e.g., STATA, R, SPSS) or computer programming (e.g. C++, Python, R) and experience working with health-related data will be advantageous
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data (e.g., using MATLAB, R, Python). Ability to write papers and reports for peer-reviewed journals. Understanding of ethical guidelines in research. Capable of planning and executing complex projects
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end users Proficient in programming or scripting languages, including Python, C++ and Java Script Ability to work independently on multiple streams of research and collaboratively across multi
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frameworks commonly used in ML research, such as Python, PyTorch, TensorFlow, and mobile development environments (e.g., Android Studio or Swift/Xcode). Demonstrated ability to conduct independent research, as
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partners. Main Duties Improve, develop, implement, and apply advanced computational tools and workflows to process, analyse, and interpret large-scale LCMS-based metabolomics datasets across multiple species