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district heating networks, within the framework of the project "Data Analysis for Peak Load Stabilisation in District Heating Networks (DAS)". The work includes: design and implementation of RL algorithms
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Networks (DAS)". The work includes: design and implementation of RL algorithms to address the challenges of peak load variations in district heating systems development and use of simulation models
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. You have a strong ability to solve problems and formulate algorithms. You also have an interest in genetics and genomics. You are organized, proactive, and can work independently as
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the research and education has a unique breadth, with large activities in classical scientific computing areas such as mathematical modeling, development and analysis of algorithms, scientific software
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focuses on combining novel genome engineering tools (e.g., CRISPR-based) and computational algorithms to enable regenerative cell therapies. Now, we are seeking a highly driven postdoctoral researcher
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, use imitation learning algorithms to learn pick-and-place actions, design HRI experiments with users, evaluate data, and share the code and benchmarks in open repositories. This postdoctoral position is
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AI methods and genetic algorithms Prior publication experience at top robotics and AI conferences (ICRA/IROS*/RSS/NIPS/CoRL) / journals (RAL/TRO/IJRR/RAM) is necessary *If you are attending IROS 2025
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data for urban characterization. The work includes developing algorithms, performing large-scale analyses, and collaborating with partners across disciplines in remote sensing, urban studies, and climate
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optimization, AI, power electronics with good publication record· Good at coding in python with different DRL algorithms training, or good at digital platform development will be a preference Knowledge of
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writing scientific papers and communicating our research advances in conferences. Methods: programming a humanoid platform using ROS2 packages, solve SLAM, use imitation learning algorithms to learn pick