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wellbeing. They will use modeling approaches to combine natural and social science data. You will focus on developing and implementing mixed modeling approaches to test pathways through which structure
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background in a technical field such as computer science, bioinformatics, mathematics, computational life sciences or related. Profound knowledge in machine learning, preferably deep learning for image data. A
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for students. Requirements We require for the position the following: A Ph.D. in the field of Applied Mathematics, Computer Science, Computational Science and Engineering, or similar. Knowledge of numerics as
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. Your qualifications ▪ Above-average university degree in electrical engineering, communications engineering, mathematics, physics (or similar) with thorough knowledge in quantum information and
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computer science with very good results - Interest on topics around the area of distributed systems and data management - Basic knowledge in distributed systems and graph algorithms is desired - Hand-on experience
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the professional provision of research and patent information to science and industry as well as the development of innovative information infrastructures, e.g. with a focus on research data management, knowledge
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mathematics, computer science, information technology, electrical engineering, physics, mechanical engineering, or a comparable qualification Sound knowledge of mathematics and physics, especially in the fields
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management, (organizational) psychology, sociology, economics, business informatics, or related subjects, • with a strong passion for entrepreneurship and/or family business research, • with a solid knowledge
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. The programme's goal is for the scholars to return to their home countries after the completion of the scholarship and share the acquired knowledge at the local centres of research. Target Group Young
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companies from all over the world, especially the USA, the UK, and Germany. Your Profile: - Ph.D. in chemistry, material science, engineering, physics, or a closely-related field - Knowledge in material