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Higher Education Code to Prevent and Eliminate Gender-Based Violence you will be asked to declare if you have been investigated for, or found to engaged in, sexual harm or gender-based violence in
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of legislation, codes of practice, guidelines and regulatory requirements relevant to animal research demonstrated understanding of the evolving regulatory environment surrounding animal research, both nationally
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Gender-Based Violence declaration, in accordance with the National Higher Education Code to Prevent and Respond to Gender-Based Violence (2025), and a Nationally Coordinated Criminal History Check. Each
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across an enterprise. Note: Employment screening will include checks required to comply with the National Higher Education Code to Prevent and Respond to Gender-based Violence. A current National Police
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continuous improvement through post-project reviews and lessons learned. Ensure compliance with UNSW policies, statutory and legislative obligations, WHS requirements, Australian Standards, Building Codes and
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University Supervisor: Dr Mega Kar Graduate Research Degree: Doctor of Philosophy (course code: 3291) Application type: Candidature only Enquiries: Dr Mega Kar, [email protected] Applications close: Monday
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 2 months ago
relevant to the role they have applied for, in accordance with the Background Checking Procedure and the National Higher Education Code to Prevent and Respond to Gender-Based Violence . Closing date: Friday
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review panels. Align with and actively demonstrate the Code of Conduct and Values. Ensure hazards and risks are identified and controlled for tasks, projects and activities that pose a health and safety
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work with Australian Synchrotron staff and the HTX Facility Manager to support implementation of HTX at the Australian Synchrotron. This involves developing and optimising the code to support and track
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manner, or we could adapt alternative forms of LLMs like JEPA. Required knowledge Good Python coding and operational experience with LLMs. Basic Bayesian understanding.