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interactions, current limiting, unbalanced loading, and faults. The other is system-level control to obtain a robust and contingency-resilient IBR system operation, such as decentralized module control
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are studying the molecular mechanisms by which these viruses, including hepatitis C virus, dengue virus, and Zika virus, activate and evade host innate immune defenses, as well as the RNA regulatory controls
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data and robust evidence on factors influencing mental and physical health in the workplace from the literature and analysis of existing high-quality datasets. Based on this evidence and building
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healthcare, computing, telecommunications, energy, and semiconductor manufacturing sectors. It also benefits from its proximity to and engagement with the Army Futures Command and the facilities and test-beds
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interested in how to leverage your expertise in synthesis and assembly to understand and control the properties of patterned or printed structured liquids, this position may be a good fit for you
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biologically inspired mechanics and control. The successful candidate will develop robot locomotion capabilities leveraging their experience in mechatronics and embedded systems, whilst incorporating principles
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optimization of numerical algorithms for these decompositions, with particular attention to their efficiency and robustness. We are looking for a candidate with expertise in AI, machine learning, and data
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an original duration of 2 years with a possibility to extend up to 5 years upon the performance and funding availability. The successful candidate is expected to develop safe and robust machine learning-based
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Development of image transformation methods and dedicated metrics documenting the level of robustness and fairness (RAF) of self-supervised learned visual features in the context of specific medical and
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environments. - Efficient and robust translation between GAI and robots with reliable two-way interfaces - Dynamics-aware mission planning and execution with multi-modal sensor data Quantum Machine Learning