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Field
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: completed scientific higher education degree (PhD) in the field(s) of Earth system science, physics, climate physics, geosciences, mathematics, computer science or a comparable field demonstrated experience
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`s degree and PhD in quantum physics, computer science, electrical engineering, mathematics or a related field Experience in quantum computer programming Experience in applying numerical methods and
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disciplines (typically mathematics, physics). For Postdocapplicants: Excellent track recordin computer science or engineering. Fluency in spoken and written English is required. Proficient in at least one
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field such as computer science, bioinformatics, mathematics, computational life sciences, or related. Profound knowledge in machine learning, preferably deep learning for image data. Experience in
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good publication track record Above-average master’s degree in computer science, electrical/ mechanical engineering, applied mathematics, or a similar engineering-oriented quantitative discipline
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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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, computer science, mathematics, physics, or a related field with an outstanding academic record. Interest in mathematical signal processing, optimization, and/or machine learning is important. Since
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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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14.12.2022, Wissenschaftliches Personal The BMBF-funded position is part of the CoMPS project, which is a multidisciplinary project combining the fields of mathematics, computer science, geophysics
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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