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, Python, SAS, or similar) fluent in English (written and spoken) proven grant-writing success and ability to secure funding strong academic track record (peer-reviewed publications, conference presentations
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data annotation (brat), Python scripting, and integrating optimization techniques such as fine-tuning, Chain-of-Thought, and Retrieval Augmented Generation to enhance LLM outputs. Experience in creating
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qualitative tools. Previous involvement in research studies in GPS and GIS technology is highly preferred. Track record of scholarly output. High proficiency in written and spoken English and Chinese (including
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informed neural networks (PINN) and explainable machine learning (EML) frameworks; experience in related technologies including large-scale data analysis, deep learning, Python, PyTorch; and the ability
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immunohistochemistry techniques. Working knowledge of SPSS for data analysis. Knowledge of Python and/or R for analyzing next-generation sequencing (NGS) results will be a distinct advantage. Experience in preparing
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well as skills in programming with Python or MATLAB. They are expected to be experts in time-frequency analysis of EEG data and building computational models using both behavioral and EEG data. In addition
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basic principles of statistics, machine learning, and LLMs. Proficiency in at least one programming/scripting language (e.g., Python, R), along with strong experiences in relevant libraries and frameworks