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generation and data analysis. About the lab The focus of Lehner lab is using massively parallel selection experiments to tackle the fundamental encoding problems of molecular biology. Towards this
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scientific or technological field related to data analysis, scientific computing or artificial intelligence. Experience Knowledge of Linux operating systems. • Basic knowledge of server
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Prof./Assoc. Professor/Assistant Professor in the School of Computing and Data Science Pok Fu Lam, Hong Kong Associate Professor, Computing Technologies (AI/ Cyber Security) Ho Chi Minh City (VN) Computing Science and Data Science - Assistant Professor Dongguan City, China
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homomorphic communication protocols for cloud quantum computing. Fault-tolerant cloud quantum computing equipped with secure quantum communication. Use of AI with reinforcement learning to improve the
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European Magnetism Association EMA | Castellon De La Plana/Castello De La Pla, Comunidad Valenciana | Spain | 7 days ago
computing paradigms such as Ising Machines. The PhD candidate's work will focus on the ultrafast dynamics of magnetic materials at the nano- and picosecond time scales using a state-of-the-art optical
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omics data. • Knowledge of environmental or molecular epidemiology. • Experience with machine learning or multimodal data integration. • Experience with high-performance computing (HPC) cluster systems
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Fundación para la gestión de la investigación Biomédica de Cádiz | Cadiz, Andalucia | Spain | 7 days ago
(CEFR). DESIRABLE REQUIREMENTS Postgraduate education: Completion of, or current enrolment in, a Master’s degree related to Mathematics or Physics Applied to Biomedicine, Data Analysis, Computing
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View less categories Discipline Biomedicine , Chemistry , Computing , Health Science , Life Science Job Type Faculty Member Employment - Hours Full time Duration Fixed term Qualification PhD Sector
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methods, classical and quantum computing approaches, and global-fit techniques for complex astrophysical signals. Research activities will be carried out jointly between The Instituto de Física Corpuscular
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train, benchmark, and develop deep learning architectures. They will work in high-performance computing environments and apply expertise in statistical mechanics, molecular dynamics, and physics. The