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. You should have a strong academic background in engineering, applied mathematics, or computer science, combined with a clear interest in scientific programming, machine learning, and data analytics
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of research results in scientific journals and conferences. Qualifications: Good understanding of solid mechanics and preferably modeling of damage and/or fracture. Experience with experimental work and data
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study programme, please see DTU's rules for the PhD education . We offer DTU is a leading technical university globally recognized for the excellence of its research, education, innovation and scientific
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use your skills to answer fundamental biological questions in health and disease. The successful candidate is expected to leverage their skills in proteomics and computational analysis to interrogate
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according to best practices on FAIR data, AI, HPC and quantum computers. Our expectations of you We imagine you hold a master’s degree in computer science, Engineering, Computational Science, electrical
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in machine learning and artificial intelligence Experience with numerical analysis and scientific computing Knowledge of power systems and renewable energy technologies Experience in power system
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streams—including data streaming to cloud databases, scientific visualization, and integration of machine learning workflows. Development of additional modules within commercial FE software (ABAQUS, MSC
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background in Computer Science, Informatics Engineering, Mathematical Modeling, Computational Urban Science, Transport Modeling or equivalent, or a similar degree with an academic level equivalent to a two