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to discover pathway‑level disease mechanisms. Build reproducible pipelines in R/Python Integrate proteomic signatures with neuroimaging, cognitive and neuropathology phenotypes. Write manuscripts, contribute
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Demonstrate proficiency in R/BioConductor and High Level (e.g. python) programming languages, Databases (SQL), development and maintaining code repositories (version control) Ability to assess resource
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programming skills in languages such as Python, MATLAB or R. Familiarity with UNIX/LINUX. High level analytical capability. Ability to communicate complex information clearly. Ability to assess resource
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. Familiarity with statistical analysis software (e.g., STATA, R, SPSS) or computer programming (e.g. C++, Python, R) and experience working with health-related data will be advantageous. The ability to work
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proficiency in R or Python. • Strong organizational and communication skills. • Proven ability to work independently as well as collaboratively in a team setting. • Must be a U.S. citizen or hold a U.S
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electrophysiology: Proficiency in whole-cell patch clamp recording, acute slice preparation, and/or cell culture electrophysiology, along with related data analysis methods using tools such as MATLAB or Python
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foundation for image analysis (e.g., affine transformations, convolutional filters, matrix and morphological operations) Programming skills in Python, MATLAB, and/or experience with ImageJ, Napari, Imaris
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(or capacity to develop understanding) in relevant field Good programming skills in a data processing and visualization language such as Python, MATLAB, R or NCL Experience with UNIX/LINUX and High
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physiology Coding proficiency (e.g., Python, R) and familiarity with deep learning tools are strong assets A strong publication record, critical thinking, and collaborative mindset Application Instructions
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language, with a strong preference for Python. Desirable criteria: Additional experience in machine learning, statistical learning theory or related fields Fluency in relevant models, techniques or methods