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mechanical design Experience with beam shaping techniques (e.g., spatial light modulators, diffractive optical elements) Proficiency in programming languages like LabVIEW, Python, MATLAB, or C++, and
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neurogenetics of Drosophila. This requires expertise in setting up and analysing behavioural tests, using appropriate analytical methods and software and skills in coding in e.g. R, MatLab, R, Python, as required
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conferences. It is essential that you hold a PhD/DPhil in computational biology, genomics, bioinformatics, computer science, statistics, or a related field together with strong programming skills in Python, R
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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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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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; supervising student projects/practicals. · Demonstrable ability to model experiments using a range of software packages, such as Python, Matlab or Mathematica. · Experience of experimental
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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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theoretical understanding of statistical machine learning methods relevant to the project: Bayesian learning, machine learning, spiking neural networks. Experience of programming (e.g. with Python) and data