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to humans and are accessible to algorithmic techniques while neural models are adaptive and learnable. The aim of this project is to develop models which combine these advantages. The project includes both
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the real world based on a seamless combination of data, mathematical models, and algorithms. Our research integrates expertise from machine learning, optimization, control theory, and applied mathematics
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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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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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develop new algorithms where needed: this may include the incorporation of genomic or other omic data 2) An important second part of the post is helping to automate components of interpretation and
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, machine learning or similar. Alternatively, you have gained essentially corresponding knowledge in another way. The applicant is expected to have good knowledge of computer science, mathematics, algorithms
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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
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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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comprehensive analysis of complex imaging mass spectrometry datasets (e.g., MALDI-MSI, DESI-MSI) using established computational frameworks Develop and implement novel algorithms and visual analytics for spatial