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Field
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. Implement AI-driven diagnostics and battery state estimation algorithms. Collaborate closely with industry stakeholders to co-develop next-generation battery control solutions, supporting commercialisation
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focused on using advanced numerical methods to explore low energy dynamics in strongly interacting quantum spin systems. The candidate will develop and implement advanced algorithms to investigate
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, and uncertainty-aware algorithms for autonomous driving systems. The position focuses on developing robust decision-making, planning, and control methods that address uncertainty arising from perception
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | about 1 month ago
candidate will develop independent and collaborative research in the area of Machine Learning, Natural Language Processing, and Algorithm Design, and work in a diverse cross-disciplinary team with researchers
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IT4Innovations National Supercomputing Center, VSB - Technical University of Ostrava | Czech | about 1 month ago
research, development, and innovation centre active in the fields of High-Performance Computing (HPC), Data Analytics (HPDA), Artificial Intelligence (AI), and Quantum Computing (QC) and their applications
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structured biological knowledge encoded in genomic graphs. The project will also deliver efficient algorithms to train these models under budget and time constraints, facilitating flexible adoption
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algorithmic aspects related to the development of highly accurate, efficient, and robust AI models capable of operating effectively within complex and dynamic radiofrequency spectral landscapes, accounting
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. The ideal candidate will have: Experience in developing novel algorithms. Experience in coding in python and preferably C/C++. Experience in frontend engineering, including but not limited
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intelligence algorithms, capable of warning far- mers in order to enable early and appropriate interventions. The proposed solution relies on the use of several complementary technologies : • Cameras
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Transparency). The main tasks will be to: Develop AI-assisted tools leveraging large language models (LLMs) to support community-based fact-checking Designi and evaluate methods to improve the robustness