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Python with demonstrable familiarity with PyTorch, experience in working on shared codebases, excellent applied math skills (especially probability theory, matrix algebra, calculus). Beyond technical
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-scale job ads datasets, spatial datasets, patents). Conduct data analysis using econometric and statistical tools. Excellent knowledge of R is expected. Good knowledge of Python, experience with modern
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in AI and machine learning – from classical approaches to large language models. You are proficient in Python and key ML libraries (e.g. scikit-learn, PyTorch, LLM APIs), and you have a track record of
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to process data and/or answer quantitative research questions (e.g., but not limited to applications written in either R, Python, Julia, Go, Java, or C/C++). E3: Experience of scientific writing. E4: Proven
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: Essential criteria MSc. in Neuroscience, Physics, Computer Science, or a related field Strong background in computational neuroscience and data analysis Proficiency in programming (e.g., Python, MATLAB, and
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of statistics and quantitative data analysis, hands-on experience with R or Python strong interest in prototyping commitment to and interest in the design and implementation of Open Science/Open Source practices
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neuroscience and data analysis Proficiency in programming (e.g., Python, MATLAB, and similar languages) Experience with large-scale neural network simulations Experience with analysing large-scale neural
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, robust/distributed control, data-driven identification/control, numerical optimisation. Strong programming skills in at least two of the following: Julia, MATLAB, C/C++, Python. Demonstrated ability
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of working within a Unix/Linux HPC or cloud computing environment Proficiency in programming (e.g. using Linux/Python and R), command-line applications, and programming standards such as version control High
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and computational abilities • Demonstrate excellent programming ability in languages such as MATLAB or Python • Excellent communication skills across multiple disciplines • Excellent academic