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(preferably with Python). Application procedure Shortlisting is used. This means that after the deadline for applications – and with the assistance from the assessment committee chairman, and the appointment
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Experience with volumetric image data Excellent programming skills (e.g., Python, C++, MATLAB) and familiarity with scientific libraries (ITK/SimpleITK, VTK, TensorFlow/PyTorch, etc.) Ability to work
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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
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An ability to take initiative, develop, and manage research activities Proficient quantitative skills with data analysis and programming e.g. in R and python Documented experience in scientific writing and
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programming language (e.g., R, Python) Who we are At the Department of Agroecology, our main goal is to contribute to sustainable solutions to some of the world’s biggest problems within the areas of soil
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skills in Python and experience with deep learning frameworks (e.g., PyTorch); Experience with distributed systems and edge AI; Strong publication record in reputable conferences or journals relative
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, or a related field Strong experience in spatial and/or landscape modelling Proficiency in R and/or Python Experience with GIS and remote sensing Ability to work with large and heterogeneous datasets
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quantitative genetics or animal breeding Has published high-quality research in peer-reviewed journals Experience with scripting languages (e.g., R, Python, SAS) and/or genetic software (e.g., DMU, ASReml) Can
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field Knowledge of freshwater ecology and/or physical limnology Experience with numerical modelling Experience with programming languages, esp. Python, and familiarity in NumPy, SciPy and Pandas
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the following areas. You have a background in tissue-based molecular research and experience with tissue sectioning and the generation and analysis of spatial molecular data. Programming expertise in Python and R