59 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"https:" positions at Queensland University of Technology
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work integrated learning (WIL) placement struggling financially and unable to meet the costs of placement able to demonstrate genuine financial hardship have no access to savings or other means
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Machine Learning for Image Classification. Eligibility You must: We would like you to have: sound knowledge of machine learning, computer vision and image processing strong programming skills. How to apply
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scholarships based on need. Students with the greatest need will receive the highest value scholarships. About the scholarship The Learning Potential Fund provides support through scholarships and bursaries
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learning internship at a regional or rural location within the Commercial Radio & Audio network. Eligibility You must: be an Australian citizen OR New Zealand citizen OR an Australian permanent resident OR a
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of system and data confidentiality and complete any other requirements. Desirable skills: Experience in programming (C, python, or similar). Knowledge in machine learning or distributed systems. How to apply
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microfluidic fabrication and experiments 3D printing machine learning. Demonstrated programming skills (Matlab, C++, or Python). Desired Demonstrated ability to work independently and to formulate and tackle
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(e.g., C++, Unity, Python) a background or interest in human-computer interaction, gender studies, and/or construction familiarity with qualitative and quantitative research methods. How to apply We
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, commencing in 2026. Other benefits may include further personal development opportunities including: work integrated learning (WIL), and paid internships. Eligibility You must be commencing your second year of
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application enrol in a business work integrated learning or experiential learning unit (BSB305 or BSN420); unit substitutions can be considered possess a passing GPA (minimum 4.0) at the time of application be
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other enabling technologies and research. It provides an opportunity to work with and learn from world-leading researchers within QUT’s Faculty of Engineering. Through this scheme, students will be