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Field
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analysis of large data sets, statistical modeling, and knowledge of at least one programming language (e. g.: R, Python and/or Julia) are required. Experience in machine learning and image recognition
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pressure Desired Practical experience in cell culture Practical experience in chemical analysis Experience in statistical analysis and programming languages, especially R What we can offer you Trust-based
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experience in chemical analysis Experience in statistical analysis and programming languages, especially R What we can offer you Trust-based working hours 30 days’ annual leave (5-day week) plus 24 and 31
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collecting and systematizing a digital corpus of sources from Nordic countries; conducting a range of research tasks using R on this corpus; assist with organization of seminars and a workshop; and will have
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years. References: [1] R. Chikkaraddy, Single molecule ready to couple. Nat. Phys. 20, 694–695 (2024). https://doi.org/10.1038/s41567-024-02494-0 [2] R. Chikkaraddy, et al. "Single-molecule mid-infrared
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disease: Exploring risk evaluation and perception PhD Studentship: R-LINCS2 funded. The Studentship is available for a October 2025 start A PhD studentship that comprises tax-free stipend of £20,870
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reports and contributing to scientific publications. Strong verbal and written communication skills for presenting experimental findings. Additional Considerations: Previous experience working in an R&D
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written communication skills for presenting experimental findings. Additional Considerations: Previous experience working in an R&D or academic research environment. Experience with safety protocols
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has experience with programming, data analysis and visualisation using Matlab, R and/or Python. Research in a clinical setting means that flexibility with work scheduling is occasionally required (e.g
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and very good knowledge in quantitative and qualitative research methods Good knowledge of statistical software (e.g. SPSS or STATA or R or JASP) Strong commitment and the ability to work in a team