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Posting Summary Logo Posting Number STA00967PO25 Job Family Operational Analysis Job Function Business Intelligence USC Market Title IT Technical Trainer Link to USC Market Title https
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adverse events in the operating room. An existing multi-agent simulator is already in place, but this thesis aims to improve it in several ways. The first improvement involves establishing a connection
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at obtaining further academic qualification (usually PhD). Research area: Systems of interacting particles are ubiquitous in natural and social sciences. Typically, they comprise many agents that, through intra
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at the interface of biological physics, agent-based simulations and machine learning to turn quantitative imaging data into a mechanistic, testable model of spindle positioning. In particular, we expect
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. Previous experience with agent-based modelling or other simulation approaches is required. Completed a well-written master's thesis which demonstrates comfort with conceptual abstraction as well as practical
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Your Job: In the CrowdING project, you will develop agent-based movement models that realistically simulate different behaviors such as lining up, overtaking, or pushing. Based on this, you will
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essential. SUPERVISION: The incumbent will be directly supervised by Charlotte County’s Florida Sea Grant Extension Agent, with overall program oversight by the County Extension Director. This position does
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learning that enable artificial agents to acquire skills through interaction (feedback) with humans. The objectives include: the development of learning algorithms; possibly the study of their theoretical
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, physical limitations). Their activities will include: - Design and analysis of mathematical models of multi-agent systems, with an emphasis on stability, controllability, and synchronization. - Obtaining
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 5 days ago
of an OpenAI Gymnasium–compatible environment layer (a “Gym-Agro” or ”Gym-PBM abstraction). This layer will expose a standardized API (reset, step, observe, reward, done) to RL agents, manage simulation calls