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Field
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the organizational activities and implementation of the Cluster’s goals. Further information about the Cluster can be found at https://uni-tuebingen.de/en/research/core-research/cluster-of-excellence-machine-learning
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of embedded machine learning, neuromorphic hardware and deep learning accelerators. Want to get more information? Click here. What you will do Responsible for RTL design (VHDL, Verilog) of digital blocks and
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, Computer Science, or other related STEM programs. Strong understanding of mathematical modeling and simulation of dynamical systems, with a focus on time-series analysis. Experience with machine learning and deep
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-tuning simulation models of robot hands to accurately capture the physics of their real counterparts, using deep reinforcement learning to train policies for in-hand manipulation of various objects in
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existing technologies, right through to the tested prototype. The Data-based Methods team at Fraunhofer ENAS develops real-world applications using AI, machine learning and computer vision. The main focus is
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of innovative products. We develop new machines and machining strategies on behalf of our customers, optimize existing production facilities, and implement future-oriented tool concepts. Our core competencies
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Your Job: Energy systems engineering heavily relies on efficient numerical algorithms. In this HDS-LEE project, we will use machine learning (ML) along with data from previously solved problem
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adaptive robotic strategies. The work will involve the integration of: Advanced motion planning and control algorithms Multi-modal perception techniques (e.g., vision, tactile, force) Machine learning models
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involve the integration of: Advanced motion planning and control algorithms Multi-modal perception techniques (e.g., vision, tactile, force) Machine learning models for physical behavior prediction and
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At the Leibniz Institute of Plant Biochemistry in the Department of Bioorganic Chemistry a position is available for a PhD in Machine Learning for Enzyme Design (m/f/d) (Salary group E13 TV-L, part