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Field
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R and Python and be highly proficient in using R for statistical analysis, bioinformatics, data visualization, and multi-omics data analysis. The candidate should be comfortable independently
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; publications--or potential for publications--in academic journals in the field; coding proficiency, preferably in Python; excellent communication and presentation skills; self-motivation; interest in research
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data analysis (e.g., MRI, EKG) and programming (e.g., Python, MATLAB, R). Expertise in machine learning, deep learning, foundation models/LLM. Excellent quantitative and analytical skills. Strong written
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to characterize the brain network interactions using connectivity and graph theory metrics. Develop reproducible computational pipelines in MATLAB, Python, R, or similar platforms for electrophysiology processing
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the arc melting, hot rolling, and mechanical testing equipment, including I/O, sensor feedback, and data capture. Connect the PLC layer to the higher-level Python control software through industrial
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working with and manipulating large datasets with scripting languages such as Python, or compiled languages such as C++, and Fortran. Experience implementing workflows with API wrappers and software such as
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skills and strong publication records to apply. Some skills in analyzing/evaluating large data sets are highly desirable. Knowledge of an advanced programming language such as MATLAB, Python, etc. is
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experiments • Analyze imaging and behavioral datasets using MATLAB or Python • Contribute to manuscript preparation and grant development Required Qualifications • Ph.D. in Neuroscience or related field
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. Preferred: Integration of wet lab findings with computational analysis of multi-omic data (e.g., structural variants, transcriptomics) using R or Python pipelines. Mentoring and Professional Development
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data-analysis skills (e.g., Python, MATLAB, LabVIEW, or C++). Evidence of independent research productivity and a record of peer-reviewed publications. Excellent written and spoken communication skills