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-control systems. Develop swarm coordination, task allocation, multi-agent path-planning, collaborative perception, and inter-drone information-sharing algorithms. Conduct simulation, hardware-in-the-loop
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The successful PhD candidate will undertake research in the following areas: Develop deep learning algorithms for autonomous robotic navigation using dual-view image fusion and shadow-based visual perception
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optimisation. Develop model predictive control and multi-agent model predictive control algorithms for path planning under dynamic maritime conditions. Develop capacity optimisation algorithms that enable drones
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dementia or Alzheimer's disease research. (Preferred) Experience developing disease identification algorithms or prediction models. (Preferred) Knowledge of longitudinal data analysis, survival analysis
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University of Darmstadt seeks candidates at the earliest possible date for two Professorships for Algorithmic Graph Theory and Logic. The positions are limited to a period of six years and come without
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-performance optimization solvers or low-latency financial systems is preferred. 3. Core Responsibilities Assistant Professor Participate in the development of theory and algorithms for YAND-related projects
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Our research group focuses on the development of AI algorithms for industrial applications. The main scope of our activities is the optimization and automation of workflows and production systems
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Localization and Perception System based on Multi-sensor Fusion Job Description: Responsible for development of robust and reliable sensor fusion algorithms for localization and navigation algorithms of robot in
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-on learning and research opportunities. The Postdoctoral Research Associate will contribute to the development of algorithms and software that enable teams of robots to perform coordinated maneuvers, self
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of science; (b) develop novel metrics and algorithms for AI explainability; and (c) create a tight feedback loop where (a) and (b) can iteratively refine each other. As a postdoc, you will be based in the Data