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on technical NLP research: what kind of AI infrastructure could enable citizens to effectively access the communal resources (both from the public institutions and civic communities)? We are seeking
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criteria PhD qualified in relevant subject area: Machine Learning, NLP, Computer Vision or related fields. Strong publication record in AI/ML/CV or related areas. Ability to work independently and
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experience in machine learning, where experience in natural language processing (NLP) is highly desirable. • Experience or education in health data science or a health-related field is a plus. • Good
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Experience with medical AI applications, particularly oncology, genomics, imaging, or clinical NLP is a plus, but not required Experience with scalable ML infrastructure, multi-node GPU training, or
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programming. Experience with NLP. Manage and manipulate data using requested packages, such as STATA, Python, R, or MATLAB. Ensure compliance with department, University, and federal regulations
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; Specialized in NLP, text mining, and graph analytics, including the use of NLTK, spaCy, TextBlob, VADER, and transformer-based models (e.g., BERT, GPT); Familiar with social network analysis (SNA) using
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, and experienced in managing research projects with tools like Git/GitHub, ClickUp, and Jupyter Notebooks; Specialized in NLP, text mining, and graph analytics, including the use of NLTK, spaCy, TextBlob
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, and experienced in managing research projects with tools like Git/GitHub, ClickUp, and Jupyter Notebooks; Expert in NLP, text mining, and graph analytics, including the use of NLTK, spaCy, TextBlob
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ggplot2, and experienced in managing research projects with tools like Git/GitHub, ClickUp, and Jupyter Notebooks; Advanced in NLP, text mining, and graph analytics, including the use of NLTK, spaCy
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counterfactual analysis. Multimodal NLP & Fusion, large language models (LLMs), cross-attention Fusion, vision-language transformers. Ontological engineering, knowledge graph construction and mining, CDE