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Machine Learning to Predict Body Image Threat from Womenswear Retail Website

Project Outline

This project aims to develop an advanced machine learning tool to predict body image threats posed by retail imagery in the online apparel industry. Integrating Computer Vision, Machine Learning, and digital  marketing, the project will provide actionable insights to mitigate negative impacts on women's mental health. The resulting AI model will be used to drive visualisations on a new apparel consumer and industry insights website, which will enhance transparency in apparel marketing and promote healthier body image standards. The expected outcomes include a robust dataset and a predictive AI tool, with significant implications for both industry practices and consumer wellbeing.

Preffered Applicant Skillset

We are looking for a PhD candidate with a strong academic background in fields such as Computer Science or Engineering. They should excel in programming languages like Python and possess a solid  grasp of mathematics, particularly in statistics. Prior research experience and a broad understanding of  artificial intelligence and machine learning techniques are essential. The candidate should demonstrate  critical thinking, creativity, and effective communication skills and have an interest in retail image  processing. Collaborative spirit and adaptability to new technologies are crucial and candidates must  have initiative and a passion for advancing knowledge in artificial intelligence and machine learning.

Primary Contact:
Dr Syed Zulqarnain Gilani
+618 6304 3946
s.gilani@ecu.edu.au

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