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wind energy systems. In particular, experience in one or more of the following areas will be considered highly beneficial: Scientific programming in Python or MATLAB Structural mechanics, reliability
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of advanced wind turbine components. Experience in one or more of the following areas will be considered highly advantageous: Scientific programming in Python or MATLAB Probabilistic methods, Bayesian inference
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analysis. Experience with programming tools like Python and energy system modelling tools like PYPSA is considered an advantage. The successful candidate should possess a curious and interdisciplinary
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Engineering, Machine Learning, Artificial Intelligence, Computational Linguistics, or a related field) • Strong programming skills (e.g., Python) • Strong skills in machine learning, deep learning and modern
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bioinformatics including NGS (Nanopore, Illumina, PacBio) Experience with automation and coding in Python or other programing languages Experience with protein software tools like AlphaFold3, Boltz2, PyMOL
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candidate is expected to hold: A master degree in biomedical engineering or computer science, Excellent programming skills (Python). Experience with data curation, large-scale datasets, and machine learning
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, material processing, and/or atomistic simulations is an advantage. Excellent analytical skills and proficiency in scientific programming (e.g. in python) are an advantage. Excellent oral and written
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, preferably with a background in behavioral neuroscience or signal processing (especially of bioacoustics data) - Programming experience (e.g. Python, R, Matlab, etc.) - Strong communication and
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to evolve classical communication networks to support both traditional data and the unique requirements of quantum information systems (https://www.classique.aau.dk). CLASSIQUE will address a suite of
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with Robotics Excellent programmer in Java / C / Python / ROS or equivalent Excellent at using Machine Learning software, e.g. PyTorch / TensorFlow / Scikit Learn Highly knowledgeable in mathematical