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web technologies Experience in teaching bioinformatics Previous experience with AI and/or machine learning approaches Interest in reproductive health and/or development of clinical tools and algorithms
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Role type: Full-time (1FTE), Fixed-term for 4 years Faculty: The Faculty of Education Salary: Level B - $122,212 to $145,121 p.a. plus 17% super Advance pioneering research in Childhood Studies and Early Years, contributing to high-impact scholarship, publications, and engagement that address...
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inversion techniques and signal processing. Strong programming skills, Proficiency in scientific computing (e.g. Python, MATLAB, or similar) for algorithm development and data handling. Experience with sensor
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Federated learning (FL) is a privacy-preserving distributed learning paradigm that allows different clients to create a shared AI models without having to share their data. Despite these advantages
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behind this efficiency by developing a general model of wing mechanosensing, revealing how sensor distribution and morphology have co-evolved with flight dynamics. The successful applicant will: Measure
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per year (pro-rata) for professional development. This entitlement, from the Concordat to Support the Career Development of Researchers , applies to Postdocs, Research Assistants, Research and Teaching
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(hiPSCs), cardiomyocytes, metabolism About the project We are recruiting a postdoc (established or newly graduated from their PhD) who has an exceptional ‘can-do’ attitude, with drive and enthusiasm to push
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per year (pro-rata) for professional development. This entitlement, from the Concordat to Support the Career Development of Researchers , applies to Postdocs, Research Assistants, Research and Teaching
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will work closely with the Principal Investigator (PI), Co-PI, and the research team to develop deep learning-based computer vision algorithms and software for object detection, classification, and
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. The successful applicant will use state of the art inference algorithms to design, use and share the findings of epidemiological models that integrate across large and diverse datasets including capture-mark