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bioinformatics support, and training and networking supports through our leading role in the Canadian Islet Research and Training Network (www.islets.ca ). Duties Specific duties will depend on the project focus
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training, as well as career development support Joining ISTA’s and the NOMIS Foundation’s global networks of exceptional, pioneering researchers Proposals are invited in the following fields: Biology
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will develop and apply methods to transform omics data into networks and executable models, collaborating closely with experts across the Petsalaki and Sheriff groups, Open Targets, EMBL-EBI, and the
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leading university, CBE provides an excellent educational experience for our students. Our global alumni network reaches the world's leading companies, policy agencies and universities. We strongly believe
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, centralized builds, strengthen local energy security, and advance inclusive pathways to net-zero electricity while producing peer-reviewed science and policy guidance for scalable, community-centred energy
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-life environments. The Role: As Research Fellow on the COG-MHEAR project, you will have the opportunity to use your strong background in deep neural networks and multimodal hearing-aid signal processing
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 27 days ago
network reaches the world's leading companies, policy agencies and universities. We strongly believe that the way in which we operate is defined by our Values and Behaviours and encourage you to apply
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, data science, differential equations, mathematical logic, mathematical physics, numerical analysis, neural networks, representation theory, and topology, with potential interdisciplinary applications
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Recruitment at shanghai.faculty.recruitment@nyu.edu . About NYU Shanghai NYU Shanghai is the third degree-granting campus within New York University?s Global Network. It is the first higher education joint
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-photonic computing architectures; Silicon-photonic network architectures Machine Learning Algorithms/Systems: Experience in design and use of ML algorithms; Experience in using ML for designing computing