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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | about 1 month ago
FTE) and/or Web Development (0.5 FTE). The position can be offered as one full-time role or two part-time appointments for a fixed term of 17 months, commencing around November 2025. The Fellow(s) will
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applications in diverse disciplines. The Fellows program aims to identify and train intellectual leaders to shape the field of physical artificial intelligence and its applications. The program provides
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tools (e.g. kneadata, metaphlan2, HUMAnN) Experience working in high performance computing cluster Experience in AI/ML, cloud computing, web development are assets Hiring Institution: LKC
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pilot context. The work plan consists of the following activities: 1) Analysis and specification • Study of the legal domain supported by AI4JURIS and the technologies in use. • Development of priority
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Application Deadline 28 Sep 2025 - 00:00 (UTC) Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff
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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 17 hours ago
composition and performance. The program concentrates on work that brings cutting edge AI to bear on research in science or music, to advance both the research area and the development of relevant AI methods
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. Working plan: Objectives and Work Plan: Production of animated educational videos in microbiology Development of laboratory tutorial videos in microbiology/microbiomes Recording, editing, and post
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pressing aged care challenges: the safe and person-centred deprescribing of medications for older adults in Residential Aged Care (RAC). The successful candidate will play a key role in developing
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-web-application-att… (6)https://www.kaggle.com/datasets/dhoogla/bccc-cpacket-cloud-ddos-2024/da… The work plan consists of the following activities: 1) Conduct literature review on cyberattacks and
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plan: The work consists of developing models for the prediction of biological control agents (BCAs), using different approaches: Machine Learning (random forests, support vector machines, lasso), Deep