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-generation observatories such as the Einstein Telescope and the LISA mission. Research duties will involve scientific programming, high-performance computing (HPC), algorithm development and analysing data
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School graduates over a thousand students who are ready to take on great ambitions and challenges. For more details, please view: https://www.ntu.edu.sg/eee We are seeking a highly motivated Research
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activities: • Develop a comprehensive model for selected structures, utilizing finite-difference time-domain (FDTD) electromagnetic simulations and iterative algorithms. • Create a physics-based generative
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Systems At the Institute of Climate and Energy Research – Energy Systems Engineering (ICE-1), our focus is on developing models and algorithms for simulating and optimising decentralised, integrated energy
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review. You will possess master level quality, accuracy, speed and knowledge for your assigned specialist area and execute reflex testing algorithms. Work schedule: 100% FTE Monay – Friday: 8:30 - 5:00pm
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INESC COIMBRA - INSTITUTO DE ENGENHARIA DE SISTEMAS E COMPUTADORES DE COIMBRA | Portugal | 3 months ago
information is available at: https://www.dges.gov.pt/pt/pagina/reconhecimento?plid=374 . Work plan and objectives to be achieved: The objective of this project is to study and develop advanced methodologies
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of optimization algorithms (desirable) Ability for integration into the department’s research profile and in particular into interdisciplinary cooperation projects (SFB MR-DYNAMO) Very good command of english
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Roman Ground Data System, providing algorithm and software development for spectroscopic and Galactic Bulge Time Domain Survey data processing. In addition, the SSC will support the operations
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structures, data transformation, algorithms, and data output by using appropriate computer language/tools to provide technical solution for application development tasks. Assist with documentation of code and
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constraints. The postdoc will work at the interface of reinforcement learning and computational epidemiology, focusing on the development of new reinforcement learning algorithms. The project will consider