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Center for Drug Evaluation and Research (CDER) | Silver Spring, Maryland | United States | about 7 hours ago
language processing (NLP) to automate FDA’s review of these qualitative responses, potentially providing both more accurate and efficient review of consumer data. Learning Objectives: Under the guidance of a mentor
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skills, including statistical analysis using R, Python, SPSS, Stata, or equivalent software. • Experience with computational social science methods, including NLP, machine learning, LLMs, social media
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for SOZO users. This work intersects with the Nunez Lab's expertise in clinical NLP, generative AI, and retrieval-augmented generation applied to healthcare and life sciences. RESPONSIBILITIES Reporting
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, and be highly proficient in Python, Large-Language Models and Natural Language Processing. Qualifications • PhD in Computer Science, especially in the context of NLP. • Coding
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managing social media datasets and metadata from the 2020 and 2024 US Presidential elections and the 2024 UK General Election. Designing, implementing and evaluating NLP and machine-learning approaches
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managing social media datasets and metadata from the 2020 and 2024 US Presidential elections and the 2024 UK General Election. Designing, implementing and evaluating NLP and machine-learning approaches
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will join Prof. Annika Schoene’s research group (https://meronymlabs.com/) in Charlotte, North Carolina, and contribute to research at the intersection of NLP methods, AI safety, and high-risk
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Science, Biostatistics, or a closely related area. Strong ML/deep learning foundation plus expertise in at least one of: multimodal learning, time-series modeling, or NLP. Demonstrated working experience
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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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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, VADER, and