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Field
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mathematics Proficient in programming (Python and C++) Fluent in written and spoken English; knowledge of German is an asset Strong analytical and independent working style Excellent teamwork and communication
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electrical engineering, computational engineering, or a related discipline A strong foundation in power system modelling and simulation Solid programming skills (Python, C++, or comparable languages) Interest
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engineering Very strong mathematical and algorithmic background Programming experience (Python, C++, etc.) Familiarity with parallel programming frameworks (e.g. MPI, CUDA) Fluent in written and spoken English
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(e.g. Python, R) or a universal programming language (e.g. C#, Java, C++, Rust) Knowledge of the use of relational and non-relational databases Very good English skills (written and spoken) High
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with emerging memory devices Experience with simulation tools (LTspice, Cadence, MATLAB, Python) Interest in brain-inspired computation, energy-efficient hardware, and experimental validation Ability
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analytical programming language (e.g., Python, R) or a universal programming language (e.g., C#, Java, C++, Rust) Knowledge of the use of relational and non-relational databases Very good English skills
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electrical or mechanical engineering Strong mathematical skills Experience in modelling energy systems Very good knowledge and experience in programming (e.g. Python, Matlab, C, C++) Fluent in written and
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quantitative medical imaging Proficient programming skills in at least one object-oriented language (e.g., C++, Python) and broad understanding of common programming paradigms, including object-oriented design
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related discipline background in one or more of the following areas is desired: X-ray or electron imaging techniques, and image processing proficiency in programming languages such as Python and experience
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for mathematics Experience with programming (e.g. Python, C++, CUDA etc.) Knowledge of information theory Good reasons to join: Look forward to a unique working environment on our international research campus