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. Experience analyzing large-scale datasets (e.g., scRNA-seq, TCR/BCR sequencing) and familiarity with R or Python are highly desired. Personal qualities: We seek a candidate who is intellectually curious
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employees and over 70% hold a doctoral degree. We have 7 Bachelor’s programmes and 3 Master’s programmes offered. We have strong focus on R&D in energy, materials, and ocean/marine technology, state
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models, machine learning, and/or programming in R or equivalent programs is an advantage but not a requirement. Alongside developing own research ideas, applicants should be capable of turning those ideas
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models, machine learning, and/or programming in R or equivalent programs is an advantage but not a requirement. The evaluation of applicants primarily hinges on their documented academic qualifications and
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. Computational & Data Analysis: Proficiency with software such as FlowJo and GraphPad Prism is expected. Experience analyzing large-scale datasets (e.g., scRNA-seq, TCR/BCR sequencing) and familiarity with R
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modelling, preferably in R Fluent oral and written communication skills in English. Relevant and significant scientific publications in respected journals, at the level of the career status of the applicant
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analysis is a requirement Experience in using relevant software to perform complex tasks, e.g. R, ArcGIS, and Python is a requirement Experience in the mapping and modelling of ecosystem services is an
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CT core scanning, as well as grain size analysis) is a requirement. Experience with (geostatistical) data analysis approaches (at least Excel and ArcGIS, but preferably also R and Grapher or similar
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relevant programming languages (e.g., Python, MATLAB, R) is a requirement. Familiarity with downscaling and bias correction of climate data (e.g., from CMIP/PMIP) is an advantage. Experience with
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science, is a requirement Applicants must possess strong skills in the management and analysis of ecological or biodiversity data using R. Experience (for example, a master’s project or internship) working