127 distributed-algorithm-"Meta"-"Meta"-"Meta" positions at Nanyang Technological University in Singapore
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language processing, reinforcement learning, deep learning, and distributed computing. We aim to create impactful applications spanning various strategic areas in partnership with academic, industry, and government
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and dynamic models. Development of optimization algorithms for the unique operational characteristics of the onshore microgrids. Development energy management system including frontend and backend. Job
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and analyze new and existing modes of operation. Formulate cryptographic security notions. Write security proofs for cryptographic algorithms. Job Requirements: Bachelor’s or equivalent (for PO and
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Responsibilities: Develop novel quantum reinforcement learning (QRL) algorithms using variational quantum circuits (VQCs), focusing on the multi-agent setting. Design and implement efficient credit assignment
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: Writing, debugging, optimizing and testing of source code with an emphasis on audio applications. Maintenance and improvement of existing audio algorithm code base including noise reduction, acoustic echo
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Responsibilities: Identify the weakness of existing watermarking and adversarial protection methods Develop new deep learning algorithms or improve existing algorithms to address the weaknesses. Prepare codes and
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. Experience in matlab, MEEP, RCWA and other softwares and algorithms. Excellent publication track records. Good understanding of nonlinear and quantum optics. Strong knowledge of optical physics, while
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, development of algorithms, publications and/or patents. Strong algorithm development and programming skills in MATLAB/Pyton and C++ Working knowledge of state of the art machine learning techniques Familiarity
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instructing or supervision of labs and tutorials. Prior teaching experience is preferred for candidates. It would be good if the candidate can also explore areas such as multimodal algorithms/techniques
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algorithms, and innovative mechanical design to replicate the remarkable flight capabilities observed in nature. The successful candidate will be part of a dynamic, multidisciplinary team of experts in