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- Knowledge in programming in Python or R - Familiarity with machine learning or deep learning methods is a plus - Interest in plant genomics, evolutionary biology, or comparative genomics - Proficient in
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QGG - Aarhus University seeks a postdoc researcher in sustainable breeding: developing simulation...
or Population Genetics. Proficient in R and Python programming is essential. Familiar with breeding programs and breeding goals. A collaborative colleague and a good communicator. Experience in collaborating with
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computational scientific workflows. Experience with scientific programming (Python or similar) Experience working in Linux-based computational environments Documented experience with high-performance computing
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candidate who has: A PhD in hydrology, environmental engineering, environmental science, geography, ecology, or a related field Strong experience in hydrological modelling Proficiency in R and/or Python
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, genetics and physiology Experience with bioinformatics and coding in Python or other programing language Experience with protein software tools like AlphaFold3, Boltz2, PyMOL, Chimera, etc. Interest in
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optimization is considered a strong advantage. Experience with Python scripting for data analysis is considered valuable. A strong commitment to research. Enthusiasm for working with research students
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field that provides a sufficient degree of background in computer science, artificial intelligence, mathematics and data science. Fluency in English, Python, and C/C plus plus are required. Experience
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methods, omics data analysis, and spatial tools is highly valued. Programming expertise in Python and/or R is essential. As a person you demonstrate high ambitions. You are equally innovative – and result
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record in peer-reviewed international journals Experience with remote sensing, LiDAR, and GIS applications Programming skills in Python Background in LiDAR point-cloud analysis and vegetation structure
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Postdoctoral position in the development of an AI-based phenotyping system for high-throughput sc...
pests, or high-throughput phenotyping Solid background in mathematics and scientific programming (R, Python, etc.) along with effective logical reasoning skills Experience with high-performance computing