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, Python and/or R, and ability to manage and structure large datasets is essential. Interest/skills in application of AI methods to clinical data is an advantage. Stipend 2: Genetic Risk Communication and
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skills, Experience in programming in Python or another language, e.g., in C++, Matlab, R, Familiarity with basic concepts of dynamical systems, Knowledge of wind turbine dynamics is a plus, Curiosity to
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, or Python. You will also be able to shape your own research. This includes primary data collection through surveys, or qualitative or quantitative interviews. Working as a PhD student requires the ability
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computational chemistry or physics will be preferred, but candidates with a solid background in statistics, computer science, and/or mathematics are also encouraged to apply. Programming skills (e.g., Python
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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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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
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process modelling, See further information at https://endure.dtu.dk/ and https://cordis.europa.eu/project/id/101227649 . Responsibilities Your overall purpose will be to develop, model, and validate a
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or another 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
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the interdisciplinary lab to bridge environmental concerns and creative design processes. • Investigate the creative process at the intersection of LCA, AI, and early design phases. • Merge Python-based approaches