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Field
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Research Translation & Dissemination Collaborate with researchers and domain experts to translate scientific requirements into technical implementations Professionalize and optimize algorithms and software
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Systems Engineering (ICE-1), our focus is on developing models and algorithms for simulating and optimizing decentralized, integrated energy systems. These systems are characterized by the high spatial and
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highly motivated researchers in all areas of the field, including but not limited to: quantum algorithms and complexity; quantum information theory; quantum cryptography; quantum information in many-body
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in the laboratory Document and evaluate experimental and simulation results Develop and validate machine learning and deep learning algorithms for photonic sensing applications What you contribute
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Develop event-driven algorithms and software components for autonomous experiment control and adaptive image acquisition Build scalable, maintainable, and open-source software for high-throughput image
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methods, Machine Learning algorithms, and prototypical Energy Management systems (EMS) controlling complex energy systems like buildings, electricity distribution grids and thermal energy systems for a
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, randomized data structures, high-performance computing, and quantum algorithms. Beyond this research, we aim to support computational thinking and computational problem-solving in the Earth sciences at large
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Faculty of Medicine of the University of Cologne | German Cancer Research Center (DKFZ) | Gronau Westfalen, Nordrhein Westfalen | Germany | 3 months ago
research division within the NCT. You will analyze comprehensive, high-quality datasets and develop algorithms for the NCT-IIT program. In particular, machine learning methods should be developed to better
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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
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Isaac Sim, ensuring realistic physics for hybrid locomotion. You will develop and train RL algorithms for hybrid locomotion tasks, including transitioning between locomotion modes and balancing on uneven