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Responsibilities: Develop novel quantum reinforcement learning (QRL) algorithms using variational quantum circuits (VQCs), focusing on the multi-agent setting. Design and implement efficient credit assignment
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state management and asynchronous updates (WebSocket/polling) Proficient in REST API integration and basic UX design Knowledge on GIS/aviation data (e.g. GeoJSON visualization, radar overlays) is
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interact with artificially intelligent systems, with a focus on social, cognitive, and ethical dimensions of these interactions. As Artificial Intelligence (AI) agents increasingly exhibit autonomy
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detection, summarisation, LLM agents) to enhance workflows. Qualifications What You’ll Bring • 2–4 years of experience in workflow automation, data engineering, or systems integration. • Hands-on experience
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Responsibilities: Develop and refine LLM-powered agents capable of understanding user intent, adapting to context, and executing repetitive tasks without requiring traditional programming knowledge. Conduct
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microsimulation, cost-effectiveness modelling, or agent-based models is highly desirable; • Experience with C++ or Python is highly desirable. Attributes • Strong analytic and problem-solving skills, with
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.) pertaining to use of hazardous materials, infectious agents, and operation of ABSL3 and BSL2 laboratories. Perform other Ad Hoc related duties as assigned for the operation of the facility. Qualifications
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also mentor Junior PIs, postdocs and PhD students. The Senior Principal Scientist position is equivalent to that of an Associate/Full Professor in the university system. The successful candidate can look
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deliver practical AI solutions based on University’s generative AI tools and platform (e.g. no code AI Agent builder and APIs). • Stay current with industry developments in the generative AI space and
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the use of education, exercise, manual therapy, electro-physical agents, technology or any other treatment for those purposes (Allied Health Professions Act 2011). Where to apply Website https