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an experience in technology-assisted monitoring or computational image analysis. Expected start date and duration of employment The position will start in June 2026, with exact starting date as agreed between
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Join us at the Department of Electrical and Computer Engineering at Aarhus University for a postdoctoral position focused on deep learning based analysis of remote sensing data for groundwater
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tools capable of addressing fundamental questions in biodiversity and conservation. Your profile We are looking for candidates with strong skills in computer vision and image‑based data analysis, combined
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research of high international quality, including publication Transcriptomics and molecular analysis of skeletal muscle Analysis of signaling pathways linking muscle excitability to gene regulation
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, or scientific publications Experience in statistical analysis of data including univariate, multivariate statistics Science communication skills proven publication record in international peer-reviewed journals
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/experimental design & analysis of complex research data. Honesty and integrity The ability to take individual responsibility for planning & undertaking own work, according to clinical and scientific deadlines
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simultaneously. By doing so, the project uncovers key pathways and mechanisms in prostate cancer progression. This will be achieved by analyzing samples using spatial transcriptional and proteomic analysis in
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underlying greenhouse gas fluxes Support training of young researchers in using biogeochemical observations and data analysis Write and contribute to international peer-reviewed publications Contribute
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scientific journals Research experience in some of the areas of fungal transformation, CRISP/Cas9 modification of fungal genes, analysis of metabarcoding data, and soil microbiology. Additional qualifications
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@au.dk) Applicants must have a relevant PhD degree in biology, biogeochemistry, hydrology, glaciology, oceanography, geoscience or physics. Field experience, data analysis and programming (e.g., python