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at the intersection of mitochondrial biology, functional genomics, and machine learning. This interdisciplinary initiative focuses on discovering, decoding and engineering mitochondrial microproteins (mito-MPs) with
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programming languages such as C and Python Proficiency in deep learning frameworks such as Pytorch and Tensorflow Knowledge in imaging and computing device and equipment Good written and oral
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Responsibilities: Conduct research on the design and analysis of scalable machine learning systems using convex/nonconvex optimization and federated learning methods. Develop algorithms and prototypes
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on emerging privacy-preserving techniques such as homomorphic encryption, secure multi-party computation and federate learning. Key Responsibilities: Conduct advanced research in the areas of privacy-preserving
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., • Interest in developing risk prediction models via deep learning/machine learning. • Have strong background in DL, EEG data and programming for the implementation of proposed methods. Apply now
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-language-action learning, enabling seamless integration from human instructions to robotic actions in complex mobile manipulation scenarios. Qualifications • Ph.D. Degree in a relevant discipline, e.g
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Responsibilities: Conduct programming and software development for data management. Design and implement machine learning models for optimizing data management. Conduct experiments and evaluations of the designed
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requirements: PhD Degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field, obtained within the last five year Research Experience in one or more of the following
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for Quantum Technologies (CQT) in Singapore brings together physicists, computer scientists and engineers to do basic research on quantum physics and to build devices based on quantum phenomena. Experts in
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of machine learning, simulation-driven testing, and iterative calibration based on real-world datasets. Contribute to scholarly publications, technical documentation, and progress reports required by funding