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or similar, obtained by the start date Experience in modeling using Python, MATLAB or similar Basic programming skills Proficiency in scientific English (written and spoken) Willingness to spend several months
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statistical modelling, Solid skills in computer programming for data science (e.g. R, Python), Experience with real-world data analysis tasks, Good communication skills in English, both verbal and written
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to provide visa sponsorship for this position. Basic Qualifications: Proficiency in coding (Python) and deep learning frameworks (PyTorch) with a drive to enhance these skills. Familiarity with one of the AI
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networks for multimodal image analysis will be essential, as well as expertise in Python and C/C++ for scientific computing, and in ML/DL frameworks like TensorFlow, PyTorch, Keras, and Scikit-learn. A
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or experience of using Stata, R, Python, or similar. Knowledge of C++ would be advantageous but not essential. Ability to communicate complex information clearly. Excellent ability to work as a team and
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of R or Python), along with writing, presentation and communication abilities. Prior experience working with computing clusters or remote servers is desirable. The fund would be available from 1st
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learning libraries and toolkits comfortably Strong software development skills with programing experiences in Python, C++, and/or Fortran Good communication and writing skills in English. Desirable
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sufficient specialist knowledge in transcriptomics and NGS sequencing as well as the essential computational skills (R, Unix or Python) to develop research programmes in this area, and familiarity with
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neural networks for multimodal image analysis will be essential, as well as expertise in Python and C/C++ for scientific computing, and in ML/DL frameworks like TensorFlow, PyTorch, Keras, and Scikit-learn
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of COMPFOR 131, an introductory course on the Python language aimed at students pursuing natural science majors. The instructor would also teach an additional course, either a section of an existing COMPFOR