542 embedded-system "https:" "https:" "https:" "https:" uni jobs at Monash University in Australia
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degree. It is named in honour of Thea Pärnamäe, a pharmacist in Sweden who was born in rural Estonia in January 1927 fled to Sweden in 1944 as a refugee of World War II. Upon completion of her secondary
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their performance evaluated in terms of classification accuracy, computational speed, and overall usability. Required knowledge Deep learning (CNNs, Transformers) and computer vision Knowledge distillation for model
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to reproducible research, critical analysis, and publication Experience with deep learning, audio analysis, or affective computing is advantageous but not mandatory.
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accurately and on time. The position also oversees resources, stakeholder engagement and team coordination, while providing strategic advice and strengthening program systems and processes. We are seeking
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responsible for end-to-end program planning, coordination and delivery, ensuring training is implemented to agreed quality standards and contractual requirements. Acting as a key liaison between the MIRRA
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expertise. That’s why we champion an inclusive and respectful workplace culture where everyone is supported to succeed. Some 20,000 staff work for Monash around the world. We have 95,000 students, four
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University as our next Media and Communications Adviser and play a leading role in shaping and amplifying the University’s global narrative. This is a unique opportunity to position one of the world’s leading
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Monash Indigenous Research Award Monash Indigenous Research Awards (MIRA) is part of a support package provided by Monash University to support Indigenous Australian students undertaking Research
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University is committed to increasing university participation of students from communities under-represented in higher education. As part of this mission, we are seeking an experienced and dynamic Senior
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The primary objective of this project is to enhance Large Language Models (LLMs) by incorporating software knowledge documentation. Our approach involves utilizing existing LLMs and refining them