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Python/R and Linux/UNIX, or expertise in structural variant analysis with motivation to upskill computationally. Experience in cancer genomics/epigenomics and high-throughput sequencing. Proven track
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appreciated Ability to engage with interdisciplinary teams involving statisticians, computer scientists, and climate experts Programming experience in a scientific computing language (e.g., Python, Fortran
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scientific discipline. Experience in developing and running an atmospheric transport model. Experience in interpreting data. Experience with FORTRAN and Python computer languages. Proven ability to work
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; proven competence in programming methods like Python; evidence of working well as part of a multidisciplinary research team. Informal enquiries may be addressed to Professor Tingting Zhu (email
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research, deep learning and biomedical image analysis are essential. Strong programming skills in Python and a keen interest in cross-disciplinary research are also required. Informal enquiries may be
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., Python, C++, or embedded systems). Strong interpersonal and intercultural skills, with the ability to engage rural communities. Willingness and ability to travel frequently for extended fieldwork in Kenya
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fractionation (i.e. surface biotinylating, gradient centrifugation, and be proficient in advanced data analysis (i.e. R, Python). Excellent analytical, organisational, and problem-solving skills are essential
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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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completion), along with relevant experience. You must also have expertise in precision physiological recording, signal processing, and artefact suppression techniques, as well as proficiency in MATLAB, Python
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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