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. Beneficial previous experience could include (but is not limited to): robotics and autonomous systems development, environmental science fieldwork, electronics design, and data science. Knowledge of Python, C
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of computer vision and machine learning. Previous experience of real time systems development in Python, OpenCV, PyTorch and deep learning are essential. Experience of C/C++/C#, TensorFlow would be beneficial
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and programming skills and experience of computer vision and machine learning. Previous experience of real time systems development in Python, OpenCV, PyTorch and deep learning are essential. Experience
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development, environmental science fieldwork, electronics design, and data science. Knowledge of Python, C++, Matlab or ROS would be of benefit. The project involves extensive fieldwork, and candidates should
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experience for example with python, fortran, C++ or others. Experience in modeling spectroscopic observables. Experience in quantum and semi-classical dynamics As a founding signatory of the Athena SWAN
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, relevant experience in computer-based statistical analysis and presentation of results, demonstrated proficiency in a coding language used for data analysis, such as Python or R, strong quantitative skills
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, relevant experience in computer-based statistical analysis and presentation of results, demonstrated proficiency in a coding language used for data analysis, such as Python or R, strong quantitative skills
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time experiments. Experience of working in an interdisciplinary team. Experience with supervising and mentoring more junior researchers. Beneficial Criteria Experience in coding (e.g. Python, C, Fortran
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. Beneficial previous experience could include (but is not limited to): robotics and autonomous systems development, environmental science fieldwork, electronics design, and data science. Knowledge of Python, C
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Python or a similar system. A4 Knowledge of integrating Design-Make-Test-Analyze (DMTA) cycles for drug discovery with automated chemical synthesis systems. A5 Knowledge of automated solid phase synthesis