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Field
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requirements for admission to the PhD programme Experience implementing and modifying deep learning architectures. Working knowledge of Python and a modern deep learning framework. Strong programming skills in
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candidates must be within numerical methods for ODEs and PDEs. A solid background in both the following fields is required: Numerical analysis for ODEs and PDEs Scientific programming using Python, MATLAB, C
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considered an advantage. Candidates should have programming skills in Python, R, or similar languages and be motivated to develop advanced modelling tools for sustainable transport planning. Your master’s
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methods, data mining, and machine learning methods. Documented shell script, R, Python, and C programming skills. Documented experience in big data analysis and computational tool/package development
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, specifically with Python-based engineering software development and hardware interfacing. Excellent oral and written English skills Demonstrated ability to independently conduct engineering projects Demonstrated
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functional MRI Experience in programing (e.g. Matlab or Python) Proficiency in literature review and advanced statistical analyses Excellent written communication skills in English A statement of research
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. Expertise in design and analyses of fMRI data (both task and resting state-based fMRI data) Expertise in univariate analyses (e.g., SPM, FSL) and programming (e.g., Python and Matlab) Experience in
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with structures. Required competence is good programming skills in MatLab and Python, and preferably with knowledge about probabilistic analysis and statistics. Your immediate leader is Head of
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/genome biology, minimum grade B (ECTS grading scale) or equivalent. The Master’s degree must include a thesis of at least 30 ECTS. Programming skills in Python, R or equivalent scientific computing
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., Python, MATLAB, or similar languages) is advantageous. Knowledge of mathematical modelling, computational mechanics, or data science is considered an advantage. Interest in cardiovascular physiology