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English, including a track record of academic writing Relevant experience with data analysis and programming (e.g. python or R) and empirical data analysis (including statistics) Strong motivation and
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focusing on different aspects relevant to the project, for example, vegetation fires, vegetation dynamics, land use and land cover change Experience in multivariate statistics and spatio-temporal analysis
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statistical analysis using STATA or R. The evaluation will take personal qualities, such as willingness to collaborate, academic independence,and communication skills, into consideration. Terms and conditions
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machine learning and other statistical methods.All work will be carried out in a collaborative research team, requiring the sharing of expertise, open discussion of results, and the facilitation
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/engineering, veterinary medicine, and often in cooperation with subject areas: architecture, work science, economics, mathematics, computer science, statistics, etc. For more information about the department
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empirical data analysis (including statistics) Strong motivation and commitment to scientific inquiry. You are expected to be somewhat accustomed to teaching, and to demonstrate good potential within research
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single-cell RNA-seq data (specifically, on remote Linux-based computational clusters). The successful candidate will possess a good grasp of statistical analysis and complex data visualization, and
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(ImageStreamX MkII), acquiring data and developing novel analysis strategies. The project involves project management, laboratory work, data analysis and statistical processing, and manuscript writing. Where
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learning, AI, or statistical modeling. Proven ability to handle large and complex datasets, including preprocessing and integration. Strong programming skills (e.g., Python, R, MATLAB, or similar
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particle, and astroparticle physics by applying methods from quantum field theory, computational physics, statistics, and applied mathematics. Within astroparticle physics, our focus spans from