10 gis-python-"NTNU---Norwegian-University-of-Science-and-Technology" positions at Aarhus University in Denmark
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skills (ready for doing business pitches) Have a strong technical background and good understanding of the principles in AI, ML, BI and Python Be fluent in English (the job is 100% in English) Preferably
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of statistical analyses and modelling. Experience in handling and analyzing large datasets. Experience in employing high performance and cloud computing services. Knowledge in GIS. Knowledge on obtaining
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transcriptomics. You possess strong programming skills in Python, R, or another relevant language. Your experience includes working with bioinformatics tools and databases, as well as multi-omics data integration
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scientific computing and programming using Python. Good communication and language skills (the project language is English). Good teamworking skills (the project is carried out in a team of 4-6 people
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. Programming skills in Python and proficiency in deep learning frameworks (e.g., PyTorch, TensorFlow) and their use in HPC environments. A strong or emerging publication record in NLP, ML, or related disciplines
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imaging, especially in vivo imaging Coding experience in Matlab, Python or R Record of first-author publications or preprints Success in competitive funding schemes/awards Experience with inflammatory
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capability to quickly gain the ability to run a clinical study and conduct intraoral 3D scanning. Further, experience with Python programming and digital 3D meshes would be considered an advantage. As a person
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candidate has proven expertise in X-ray imaging, synchrotron experiments, and multimodal X-ray imaging, e.g. XRD or XRF computed tomography. Experience in scripting in Python or MATLAB is an advantage
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, including bias mitigation and reinforcement learning techniques. Proficiency in Python and standard NLP libraries (e.g., Hugging Face and PyTorch). CHC is a research and development unit at Aarhus University
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, electrical engineering, communication engineering, computer science, or a related field. Documented experience with deep learning techniques (e.g., CNNs, Transformers) Strong programming skills in Python and