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Field
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Python and AI-enabled methods to extract, classify, and summarize insights from unstructured data, including text, images, and other digital content. This work will help BSA detect trends, measure impact
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with electrophysiology acquisition and analysis (for example spike sorting, LFP analysis, population analyses) Strong quantitative skills and programming experience (MATLAB and or Python), including
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collaborators. For additional information about the Liao research group, please visit: https://sites.google.com/view/chentingliao/ Department Contact for Questions: Questions regarding the position or application
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(for example spike sorting, LFP analysis, population analyses) Strong quantitative skills and programming experience (MATLAB and or Python), including reproducible analysis workflows Familiarity with
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, progression, and therapeutic response. This research is fundamental to advancing our knowledge of cancer and improving patient outcomes. See further information at the lab webpage: https://odin.mdacc.tmc.edu
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environmental and ecological data; knowledge of, or interest in, statistical data analysis using programming tools (R, Python, MATLAB, or equivalent); and the ability to work collaboratively in interdisciplinary
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experiment codebases (prefer Python). Apply causal inference and discovery frameworks to clinical questions. Translate proposed methods and frameworks into real-world clinical workflows. Contribute to grant
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(Kubernetes), serverless computing, and REST API development. Proficient in Python, with basic experience in machine learning or computer vision libraries; familiarity with Vision-Language Models (e.g., CLIP
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maintenance of equipment. Job Requirements Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Software Engineering, or a related field. Strong programming proficiency in Python and/or C
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understanding of human genetics. Knowledge of DNA and RNA sequencing analysis, of programming languages such as R, Python, or Bash script, and of bioinformatics pipelines for genomic data analysis is essential