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05.04.2023, Wissenschaftliches Personal We are the Autonomous Vehicles Systems (AVS) Lab and are interested in the algorithmic foundations of path and behaviour planning, control and automated
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an extensive safety analysis and calidation of perception algorithms in automotive. Through our work, we lay the foundation for a reliable digital future. What you will do Reliably detecting persons is crucial
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dynamics or Hamiltonian eigenstates with classical and quantum algorithms Comparison of quantum algorithms with classical baselines Analysis and documentation of results What you bring to the table Student
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control, state estimation, and path planning algorithms for single and multi-agent robotic systems (UAVs). develop and train AI models for practical applications such as real-time object detection and
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you will do Driving innovative AI research through the development and implementation, practical application, theoretical analysis and evaluation of AI algorithms Use of XAI tools to explain machine
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analysis, with possible specialisations in genomic and molecular biology techniques as well as in algorithms, statistics and artificial intelligence for molecular genetics. This is based on perspective and
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Overview Eine Druckversion dieser Ausschreibung (PDF) steht Ihnen in den weiteren Registerkarten (z.B. „Bewerbungsvoraussetzungen“) zur Verfügung. A print version of this announcement (PDF) is available in the further tabs (e.g. “Application requirements”). Programme Description The Hans Böckler...
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functionalities (GUI and web-service) Participate in field work organization, sampling plan establishment and in-situ data acquisition Your Profile PhD in environmental sciences or computer science, with a proven
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will work in a group with other students and take on specific tasks. The aim is to analyse the robot's capabilities and to implement algorithms that enable the robot to be used sensibly in applications
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) simulations and offer time-saving benefits. We are looking for a dedicated and motivated student to assist us in implementing a novel Graph Neural Network based algorithm that can act as surrogate for FEM and