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Field
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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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experience with statistical tools (e.g. in R, MatLab, or Python) are expected. The team at DTU Aqua is highly international and knowing the Danish language is not needed. You must be available for boat-based
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the development of good programming skills (Python/MATLAB or similar), good communication skills, the ability to work independently, and a willingness to engage with industrial partners. To apply, please contact
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strategies. Proficiency in statistical programming languages (R, Python, or Stata) with verifiable experience in panel data analysis. Good communication abilities for effective knowledge dissemination
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proficiency in R or Python for data analysis and modeling. Familiarity with analyzing large-scale healthcare datasets and real-world data. Experience in developing and applying simulation models, including
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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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, 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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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