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or above. have outstanding grounding in one or more relevant disciplines including cancer biology, cancer medicine, physics, chemistry, , engineering, machine learning / data science, coding. How to apply
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Martin Australia invite applications for a project under this program, advancing robotic perception systems through monitoring of their machine learning models. Run-Time Monitoring of Machine Learning
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. • be located at the agreed project location(s) and, if required, comply with the university’s external enrolment procedures. Selection criteria Skillset: Proficient in Python, machine learning, and
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Monash Education PhD Scholarship - Engineering the Future: Safety Risk Intelligence in Early Childhood Job No.: 686175 Location: Peninsula campus, Melbourne and rural Victoria Employment Type: Full
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interested in connecting spatial and spectral information to understand complex materials systems at the molecular level with machine learning. PhD Student A will work with tumour sections to develop multiple
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learning. Supervisor: Prof. Udo Bach, Department of Chemical and Biological Engineering. (Email: udo.bach@monash.edu ) Manipulating light at the nanoscale Supervisor: Dr Alison Funston, School of Chemistry
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, for instance, utilise conversational agents, computer vision, mixed reality, wearables etc. Disability, Technology, and Society: Research with a sociological or anthropological focus on the use of bespoke and/or
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We are seeking an outstanding PhD candidate to undertake a program of research within a broader NHMRC Investigator Grant entitled: Using Sleep Technologies to Better Define and Manage Insomnia. This exciting project is supported by a large, multidisciplinary team from the Flinders Health and...
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required new IEC standards relevant to the performance and lifetime of printed solar technology through developing a detailed understanding of printed solar degradation mechanisms and interactions with
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publications and research experiences in structural dynamics and structural health monitoring, especially on computer vision, image processing, machine learning, deep learning, signal processing and data