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excitations and excitonic effects using advanced Wannier-based methods * Quantum transport in polymer materials with electron–phonon coupling Full details and application instructions: https://www.ch.nat.tum.de
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graduate to work full time on a 27-month Knowledge Transfer Partnership (KTP) to develop an advanced aftermarket sensor-led condition and monitoring solution upgrade for the EDM engineering processes
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designing DNA, RNA and proteins to create nanoscale devices for applications in biotechnology and medicine. The lab invented the RNA origami method [1] and have developed basic algorithms and software for RNA
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. QLAB is a newly funded research center under the Foundation for Polish Science's International Research Agenda (MAB) programme, focused on developing scalable hybrid quantum-classical technologies
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. The QUBIC consortium will deliver disruptive innovations across three core quantum domains: Development of quantum algorithms to solve current industry-specific challenges. Advancement of quantum processors
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associate will work both independently and collaboratively to develop and apply novel deep learning algorithms and/or computational chemistry methods for small-molecule drug discovery targeting RNA
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 20 days ago
, available on https://dre.pt/application/file/a/127230968 . Workplace: The work will be developed at CEMAT of Instituto Superior Técnico, under the scientific supervision of Dr. Erida Gjini Website
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researchers Grant writing experience Experience with high performance computing (HPC) and deep learning frameworks like PyTorch Experience developing parallel algorithms and scalable workflows for HPC resources
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 5 hours ago
to): Develop machine learning algorithms that utilize fire products from geostationary satellites to better represent fire evolution and variability Develop machine learning emulators to represent forward
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developments in sensor design, dataset transmission, data analysis, and numerical modeling to distinguish between normal and abnormal features. Here, the goal is to develop machine learning algorithms