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Programming skills in Python, R, and/or GIS tools Highly valued: Background in LiDAR point-cloud analysis and vegetation structure analysis or habitat monitoring Experience applying AI or machine learning
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Programming skills in Python, R, and/or GIS tools Highly valued: Background in LiDAR point-cloud analysis and vegetation structure analysis or habitat monitoring Experience applying AI or machine learning
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control and cloud/HPC computing platforms. Familiarity with containerization (Docker). Ability to collaborate with multidisciplinary teams (e.g., biologists, clinicians, software engineers) and to
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for simulation, and data/cloud platforms. Contact For further information please contact: Professor Ulrik Pagh Schultz Lundquist ups@mmmi.sdu.dk Associate Professor Aljaz Kramberger alk@mmmi.sdu.dk Associate
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develop a digital twin model of the southwestern Baltic Sea that can be used to simulate climate scenarios and test various management measures. The work will utilize both local and cloud-based