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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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collaborative projects involving large international consortia. Our research is focused on translational research on the genomic and epigenomic characterization of various gastrointestinal cancers (GI), including
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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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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
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learning and advanced statistical modeling * Proficient programming skills in Python and/or R, experience with machine learning and omics analysis libraries (e.g., scikit-learn, TensorFlow/PyTorch
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science, drug discovery, or related fields are encouraged to apply. Strong computational backgrounds, proficiency in at least one programming language (e.g., R, Python, Perl, C++, Java) and knowledge