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Field
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across connected forest–lake ecosystems. By integrating multi-taxa field data, trait-based ecology, experiments, and advanced statistical analyses, TRACE aims to uncover how ecological processes propagate
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part in teaching and supervision at BSc and MSc level, and to take responsibility in grant application writing. We seek a candidate with knowledge of the application and analysis of Sensory & Consumer
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. Applicants with interests and experience in any of galaxy formation, Lyman-alpha absorption, ISM/CGM evolution at high redshifts, JWST NIRSpec spectroscopy, ALMA spectral data, and statistical inference
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techniques Ability to support non-bioinformaticians and deliver training in WGS data analysis. Skills in data management, visualization, and statistical analysis. Proven ability to plan and execute complex
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of strains) to in-field testing of up to 800 strains. The scale and standardized approach will create a unique foundation for advanced data analysis, including AI, machine learning, and statistical modelling
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has more than 600 students in its BSc and MSc programs, which are based on AAU's problem-based learning model. The department leverages its unique research infrastructure and lab facilities to conduct
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on complementary aspects of the project. Collaborate with the statistical post-doc on the study who will lead advanced statistical developments. Ensure methodological rigor and scientific excellence throughout all
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CFD workflows and Lagrangian particle/cell tracking to extracting actionable insights with statistical learning and AI/ML—ultimately enabling more robust scale‑up, smarter process control, and faster
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and statistical tools to identify patterns in large datasets The candidates should demonstrate evidence of self-driven and independent research capability, excellent collaboration and communication
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members to analyse data, present project findings at international conferences, and produce scientific papers. Some research-centered teaching at BSc and MSc levels as well as science outreach for public