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Take a leadership role in the development of a multi-strain Streptococcus pyogenes computational transmission model Full Time/2 Year Fixed Term Research Only Appointment, Remuneration at Academic
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 22 days ago
, integrated task and motion planning, multi-agent planning, integrated planning and learning, and reinforcement learning, with ample research collaborations with academia and industry. For further information
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stakeholders Track record of scientific creativity and problem-solving in research activities Preferred Qualifications Experience with agentic AI systems, prompt engineering, or multi-agent frameworks
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apply cutting-edge machine learning algorithms, with focus on foundation models and LLMs/agents, to analyze complex biological data. This data includes gsingle cell genomics profiles, spatial data, and
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, relative to experience. Evidence of experience that is relevant to research in one or more of the following areas: Planning under uncertainty, robot motion planning, multi-robot planning, integrated planning
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to join a three-year multi-institutional project aimed funded by Versus Arthritis focussed on developing a novel peptide-siRNA conjugate for the treatment of osteoarthritis (OA). OA is a degenerative joint
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, including autonomous robotic systems for In-space and On-orbit Servicing, Assembly, and Manufacturing (ISAM and OSAM) and space logistics. Develop and implement control algorithms for distributed multi-agent
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limited to, multi-agent search, sim-to-real, and modeling of dynamic systems with modern machine learning technique. Beyond research, the candidate will develop project ideas both independently and within a
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to time by the Project Lead. We hope you will bring: Experience of undertaking research in developing and deploying ML models (including regression, classification, deep learning, multi-agent
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candidate. We invite applications for a Postdoctoral Research Associate to join the OCEAN project (On intelligenCE And Networks: Mathematical and Algorithmic Foundations for Multi-Agent Decision-Making, https