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description You will be contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will
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. Our group develops machine learning algorithms to automatically generate discoveries from large-scale brain imaging data. We aim to uncover fundamental principles of healthy brain development
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and dynamics, which we also plan to investigate using AI-based pattern recognition algorithms. In this project, the PhD student will: Run the MIT General Circulation Model (MITgcm) together
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to the application deadline Experience from sea ice field work or polar expeditions Experience in work with oceanographic or meteorological data and models What you will do Apply, validate and improve algorithms
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programming skills. Expertise in developing computer vision and machine learning algorithms would be desirable, highly motivated and enthusiastic about advancing AI for societal impact. Qualifications A high
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Supervisors: Prof. Finn Werner – Werner Lab Website Dr. Christopher Waudby – Waudby Lab Website Abstract: RNA polymerases (RNAPs) are essential enzymes for viral replication and represent
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Structure and Laser of the Foundation for research and Technology Hellas (IESL-FORTH), in the framework of the project COLOURS (P.I. Prof. S. Sotiropoulou, Call: HORIZON-CL2-2024-HERITAGE-ECCCH-01-05- A
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, hardware-adapted optimization, and error mitigation techniques, aiming to identify requirements, limitations, and pathways for improvement of both hardware and algorithms - analyze variational ansatz
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, mathematics, data Science or related disciplines with a proven track record of expertise/expertise in tool and algorithm development and/or applied bioinformatics, who are also keen to expand our research
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of algorithms, data models, and interfaces. Research and selection of the tools and technologies to be used. • Initial development and prototyping: Start of development of the core components of the malicious