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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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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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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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for research (e.g. Python, R and RStudio or MATLAB) and using data-driven pipelines with complex bio-behavioural data. Prior knowledge or keen interest in topics at the intersection of experimental psychology
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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 Python, or demonstrated ability to rapidly acquire fluent knowledge of new programming languages, libraries, and platforms. A background and/or interest in mathematics or computer science would be
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demonstrated ability to analyse and interpret complex multidimensional data. Experience of programming in Python, or demonstrated ability to rapidly acquire fluent knowledge of new programming languages
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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
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programming (e.g. Python) and an excellent academic track record commensurate with career stage. They will also have excellent communication skills, including the ability to write for publication, present
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environments is highly desirable Programming skills in R, Python or equivalent Excellent communication skills in English High motivation for collaborative and interdisciplinary work What we offer: Work-life