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. Supervise statistics collection and support our data tracking. Track and keep updated public information on our programs in relevant channels. Handle evaluations of our programmes. Assist the rest of the team
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, (agro)ecology, or geography with strong expertise in ecological modelling or crop modeling. A strong statistical background and programming experience in R/Python is also necessary. Experience in working
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, stakeholders, and managers) Experience in data analysis and statistical tools Preferable experience with advisory work Who we are The Department of Ecoscience is engaged in research programs and advisory work
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genetics, animal breeding, statistics, or a related field. Proficiency in statistical analysis of genetic data related to insect breeding and experience in developing insect breeding strategy. Experience
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Familiarity with research data and/or GDPR Competent in the Unix shell and with experience in an HPC environment Practical experience with R and/or other statistical tools Familiarity with cloud computing
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of survey research, from planning and ethics approval, through pilot work and data collection, to statistical data analysis and write-up. Qualitative research skills and experience are an advantage but not
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, Physics, Computer Science, etc.), a strong background in Data Science, Statistics, or Machine Learning, and an interest in Biomedicine. Alternatively, a candidate with a biomedical background with some
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Topology, Probability Theory as well as in Statistics, Data Science and Operations Research. A successful candidate should have demonstrated the ability, or have the clear potential, to: Participate in and
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investigating potential vaccination strategies for poultry. Methods from classical statistics, spatial statistics, machine learning and simulation modelling may be used as necessary to meet the objectives
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beyond. Hence, we seek a proactive candidate with a strong background in statistics and economics. Your primary tasks will be to: Design workflows for quantitative societal sustainability assessment of low