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[½»Á÷] Ó¢¹úÂ×¶Ø´óѧѧԺ£¨UCL£©ÕÐÆ¸ NLP in Healthcare·½ÏòResearch Fellow

Ó¢¹úÂ×¶Ø´óѧѧԺ(ucl)£¬½¡¿µÐÅϢѧѧԺ(institute of health informatics)£¬ ÕÐÊÕnlp in healthcare·½Ïòresearch fellow. ÏêÇéÈçÏ¡£

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research fellow in healthcare using natural language processing
(grade 7: up to ¡ê46,155 per year, including london allowance)
institute of health informatics, university college london

the university college london (ucl) is a renowned global university located in the heart of london. it boasts a top-ranked population health program and computer science department according to multiple rankings. the ucl institute of health informatics (ihi) leverages and generates data to drive the science of disease prevention and improved health outcomes. its world-class research and educational offerings are immediately applicable for healthcare decision-makers, including those who are developing and evaluating innovative ai-powered interventions.
the successful candidate will collaborate with a team of experts, including dr. honghan wu, dr. kezhi li, prof. richard dobson, and other scientists and clinicians at ucl specializing in natural language processing (nlp), machine learning, and mental health. the goal is to leverage the potential of nlp to develop a cutting-edge clinical solution for mental health problems by analyzing social media postings and detecting behavioral changes before the individual is conscious of them. the project will involve conducting ai-driven sentiment analysis using techniques such as frequency and event analysis on large social media datasets. the effectiveness of the model will be evaluated and improved through a multi-month trial involving tens of participants. the outcome of this work will be a set of generic analysis tools for performing the required analysis and statistical validation of these analytical tools.
aim: extracting and processing social media datasets to build an ai model that utilizes advanced nlp algorithms to detect subtle changes in behavior and mood through sentiment and event analysis, and verifying the effectiveness in a trial.
essential requirements
        a phd (or equivalent) in an area relates to the subject area.
        relevant computer science/engineering/mathematics/physics or exceptional clinical/ bio-science undergraduate background
        python (preferred) in machine learning
preferred experience (one more multiple):
        nlp, sentiment analysis, data mining, or any quantitative subject, such as signal processing, mathematical modeling, algorithm design, strong analytical & programming skills
        electronic health record, clinical dataset analysis, mobile health, mental health
time: expecting to start from late mar.2023 to oct. 2024 the first instance
informal enquiries or formal application please attach your cv and contact dr. honghan wu (honghan.wu@ucl.ac.uk) or dr. kezhi li (ken.li@ucl.ac.uk).
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