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Field
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, sustainable, and scalable artificial intelligence technologies. The successful candidate will develop novel algorithms and system-level innovations that significantly improve the energy efficiency
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opportunity for an experienced researcher to lead the development of decentralised swarm control algorithms for underground pipe operations. You will join an international research programme funded by
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at the interface of optimization, geometry, and machine learning Designing, implementing, and testing algorithms Engaging in scientific exchange with collaboration partners of the project Preparing reports
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and make energy use more efficient. We develop novel optimization methods, Machine Learning algorithms, and prototypical Energy Management systems (EMS) controlling complex energy systems like buildings
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simulation models, conducting algorithm design, and analyzing simulation results. There may be opportunities for future implementation and experimentation with hardware. A keen interest in research and
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. The successful candidate will assist in developing novel algorithms and integrating them into robotic platforms, helping to push the boundaries of embodied intelligence in both research and practical deployment
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projects at the NGI Center. Job Description Primary Duties & Responsibilities: Implements: Algorithms and computer software for analyzing omics-based data sets [high-throughput, massively parallel genomic
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external organizations, as well as publishing work in scientific journals and presenting work at conferences. Implement software algorithms in C++ and Python in a collaborative environment. Work closely with
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and other external organizations, as well as publishing work in scientific journals and presenting work at conferences. Contribute to the first principles problem formulations, algorithm development
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disaster resilience and adaptation, leveraging algorithmic decision-making for real-time infrastructure recovery and efficient resource allocation during extreme events. Required Qualifications Applicants