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Research Infrastructure? No Offer Description Based at Australian Institute Machine Learning (AMIL), City East Campus 2 x Full-time, 2-year fixed term contracts Salary Range: $114,917 - $135,932 per annum
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 15 days ago
: PD & PEWER Level B Research Fellow_SOE.pdf Work with world-leading researchers in robotics, computer vision, and systems and control Contribute to impactful research on cutting-edge event-based sensing
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18 Mar 2026 Job Information Organisation/Company Instituto Superior Técnico Department Direção de Recursos Humanos Research Field Engineering » Computer engineering Researcher Profile First Stage
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18 Mar 2026 Job Information Organisation/Company FEUP Department Human Resources Division Research Field Engineering » Computer engineering Engineering » Electrical engineering Researcher Profile
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Academic Job Category Faculty Non Bargaining Job Title Postdoctoral Research Fellow in Machine Learning for Computational Pathology, Medical Imaging, and Clinical Text Analysis Department Bashashati
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of Safety, Economics and Planning. Department of Electrical Engineering and Computer Science conducts research in computer engineering, data science, cybernetics, electric power engineering, signal processing
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for the university and funding agencies. Job Requirements: PhD qualification degree in Computer, Electrical or Electronic Engineering or related field At least 3 years of relevant research experience in AI security
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interaction, communication, or psychology. Masters or Ph.D. in Human-Computer Interaction (HCI), Computer Science, Cyber Security, Computer/Electrical Engineering, Information Technology will be advantageous
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/Administrative Internal Number: 528713 Pay Grade/Pay Range: Minimum: $53,500 - Midpoint: $66,900 (Salaried E8) Department/Organization: 214251 - Electrical and Computer Eng Normal Work Schedule: Monday - Friday 8
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magnetic response. Development of machine learning methods for exchange-correlation functionals. Current work in the group is focused on improvements and performance optimizations for the recently developed