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Field
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, and scripting in R Practical experience with laboratory animal experiments and/or with large-scale studies of animals in the field Assessment criteria and other qualifications This is a career
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analysis and data handling (e.g., R or other relevant platforms) Experience conducting ecological fieldwork, preferably in remote or tropical environments Practical experience in laboratory techniques
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Bioinformatics, Computational Biology, Systems Biology, Computer Science, Biochemistry related to proteomics and mass spectrometry, or a related field. Strong Python and R skills for omics data processing, QC
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Experience A PhD in bioinformatics, computational biology, systems biology, or a related field, or equivalent scientific expertise Proficiency in Python and R, particularly for data analysis, visualization
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Biology, or a related discipline Proficiency in Python and R, with experience in spatial transcriptomics data analysis and high-dimensional data visualization Demonstrated experience in building and
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, R, Bash or similar) for omics data processing, QC, statistical testing, and visualization to support biological discovery Familiarity with working with Unix/Linux environments An understanding
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the time at which the appointment decision is made. To be eligible for the position, you should have: Strong skills in programming and analytical tools, particularly R, including data visualization and
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field Strong programming skills (Python, R, Bash or similar) for omics data processing, QC, statistical testing, and visualization to support biological discovery Familiarity with working with Unix/Linux
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energy system modelling and mathematical optimisation. Knowledge in propulsion and aircraft technology, including performance and conceptual design. Experience in industrial R&D or in junior academic
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of scientific publications. Documented experience in conducting register studies and managing large datasets. Good knowledge of Stata/R. Previous experience of working in multidisciplinary research groups. Basis