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with R or Python tools. Experience in processing of targeted and untargeted mass spectrometry datasets Demonstrated research competence and initiative through inernational publications in peer-reviewed
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standard imaging analysis method including use of Python (NumPy/SciPy/PyTorch/Tensorflow), Matlab, C++, version control software (e.g. git), and statistical analysis using R, SQL, etc. Familiarity with
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standard imaging analysis method including use of Python (NumPy/SciPy/PyTorch/Tensorflow), Matlab, C++, version control software (e.g. git), and statistical analysis using R, SQL, etc. Familiarity with
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CT or MRI scans. Your technical skills include Python programming and familiarity with deep learning frameworks (PyTorch or TensorFlow), along with a solid understanding of image processing techniques
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), have good organisational and communication skills and have experience running research studies in humans. Experience with data analysis and basic experience using programming languages (e.g. R, Python
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for handling and analysing large and complex geophysical datasets, including programming skills in languages such as Python or Matlab. 10. Skills in description, analysis and dating of sediment cores. 11. Skills
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industrial experts. Nice to have: Proficiency in programming languages (Python, MATLAB, or similar software) for data analysis/model automation. Prior industrial collaboration or scale-up project experience
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reaction. Expertise on data analysis with R or Python tools. Experience in processing of targeted and untargeted mass spectrometry datasets, ideally in the field of lipidomics or other omics sciences
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in systems neuroscience. Ideally you would have experience with mouse behaviour and/or Neuropixels recordings and analysis, as well as with opto/chemogenetics. Being a pro with Python/MatLab helps
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in systems neuroscience. Ideally you would have experience with mouse behaviour and/or Neuropixels recordings and analysis, as well as with opto/chemogenetics. Being a pro with Python/MatLab helps