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way of working and quick comprehension; ability to quickly familiarize yourself with new concepts Enjoy scientific work in a cross-domain context. Good knowledge of programming languages (e.g. Python, R
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knowledge of Python and FORTRAN programming, UNIX/Linux and shell script Knowledge in dealing with server-based computer structures and high-performance computers (e. g. HLRE at DKRZ) Confident handling
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, ideally in Python, with demonstrated experience in applying them in complex research or development projects Basic knowledge in Machine Learning, ideally supported by initial hands-on experience Experience
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circuit design methodologies and signal integrity analysis Deep understanding of programming languages (Python, C/C++), algorithms, and problem-solving in a dynamic tech landscape Hands-on experience in AI
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, System Verilog and programming by using Perl or Python Preferably circuit and layout design experience in Cadence Virtuoso, Tanner EDA or any other full-custom design tool Strong problem-solving and
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with (scientific) programming (Python, R or other languages) Comfortable with mathematics and analytical systems thinking Curiosity and willingness to expand their knowledge in related disciplines Very
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about the Amazon rainforest and willing to expand her/his knowledge in related disciplines Experience with programming (Python, Julia or other languages) and atmospheric transport modeling is beneficial
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, Computational Biophysics, or a closely related field Strong programming skills (e.g., Python, C/C++) Knowledge of machine learning frameworks (e.g., PyTorch, TensorFlow) Very good English language skills, ability
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code via differential testing) We focus on techniques that apply to real-world software systems. E.g., in the past, we have developed techniques that find and fix bugs in widely used Python, Java, C/C
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yourself quickly with new concepts. Enjoyment of scientific work. Very good/good programming skills (at least in Python and C++). Good written and spoken German (at least C1 level) and English. In-depth