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develop tools for ingesting, transforming, and integrating large, heterogeneous microscopy image datasets—including writing production-quality Python code to parse, validate, and transform microscopy data
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of, mechanical and electronic-circuit design, alongside fabrication methods (3D-printing, laser cutting, etc.) is expected. Strong candidates will also have software experience with coding in Python, C++, and
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writing production-quality Python code to parse, validate, and transform microscopy image data from published research papers, public databases, and internal repositories. This role requires technical
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in-vivo recordings. Perform coding-based data analysis (Python and/or MATLAB); working with and organizing big datasets (e.g. chronic in-vivo recording, videos and tracking). Optimize and troubleshoot
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opportunity for publication of this suite of tools in a methodological journal. What you bring: A degree in computational sciences or equivalent (M.Sc. or Ph.D). Experience with C# and Python programming (async
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, neuroscience, biology, mathematics, or a related field. Proficiency in Python or Julia (Matlab preferred) and strong debugging skills. Experience using GitHub for version control and organizing/publishing
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findings clearly to research team members What You Bring Bachelor’s or Master’s degree in Bioinformatics, Computational Biology, or a related quantitative field Strong programming skills in Python and R
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in a research environment a plus General languages (preferred): C++, Python, MATLAB CUDA (strongly preferred) Machine learning knowledge. e.g. logistic regression, SVM, neural network models Basic
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to ensure the seamless integration of computational and experimental workflows. Strong programming skills in Python, PyTorch, and JAX are required, along with the ability to reason about neural network
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computing experience. Proficiency running bioinformatics pipelines in R, Matlab, and/or Python. Proficiency in data analysis, data visualization, and statistical inference. Ability to perform independent