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PhD Candidate on The Future of Mixed Methods Research /Junior Lecturer in Methodology and Statistics
department Methodology and Statistics gives you the opportunity to kickstart an academic career. Your position Research: The Future of Mixed Methods Research is Rigorous, Open, and Scaleable through Automation
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(algorithms), and statistics. During this project, you will develop new methods to construct phylogenetic networks and generalize mathematical frameworks of phylogenetic network classes to tackle related
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, experimental designs and applying (multivariate) statistical techniques; excellent written and verbal communication skills in English; independence, eagerness to learn and the ability to work in an
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project stakeholders. Enthusiasm for performing field work on-station and on-farm. Strong analytical and statistical skills; experience with ecological data analysis or ecological network modelling is an
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) a statistical package (e.g., Stata or R). Excellent command of English. Applicants whose native language is not English are therefore required to demonstrate English proficiency by: proof
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quantitative/statistical and bioinformatics skills. You will coordinate collaboration by managing cross-team experiments. You will write and publish your research in leading scientific journals and communicate
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statistical skills; experience with crop modelling is an advantage. Affinity to work within a larger multi-disciplinary project, with strong project/time management skills. Proficiency in Dutch, and/or valid
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analysis, visual methods, and mix-method (statistics, other quantitative and qualitative research) skills; Strong scientific English writing skills; an experience in academic or professional publishing is a
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) a statistical package (e.g., Stata or R). Excellent command of English. Applicants whose native language is not English are therefore required to demonstrate English proficiency by: – proof
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related field, and a strong interest in biomedical applications. Experience in machine learning, statistics, or high-dimensional biological data analysis is advantageous. Ideal candidates are curious