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), on February 21st, 2024. These Doctoral Research Fellowships are intended for candidates who meet the necessary conditions to enrol in any NOVA’s Doctoral Programme, and who wish to develop research activities
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experiments and/or quasi-experimental studies in collaboration with external partners such as IEFP; Assist in the development or application of machine learning models, particularly those focused on causal
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. In this role, you will be part of the research team, working to develop and evaluate privacy-preserved Generative AI algorithms for generating synthetic Personal Identity Information (PII). This aims
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and application of fast solvers for Maxwell’s equations and nonlinear inversion algorithms that we have already developed in a previous PhD project. In addition to electromagnetic geophysics
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algorithm development, data analysis and inference, and image analysis Ability to do original and outstanding research in computational biology, and expertise in computational methods, data analysis, software
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. The successful candidate will play a pivotal role in a project centered around variational quantum algorithm in the near-term, especially on innovating advanced error mitigation or detection techniques to solve
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, the appointed candidate will work closely with the line manager to develop novel control algorithms in EAP soft robotics combining Gaussian Predictors, hands-on laboratory experiments and JULIA computing
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 month ago
Python or R is preferred. Ability to analyze multi-omic data, including microbiome data, would be an advantage. Ability to build algorithms and data pipelines would be ideal. Create a Job Match for Similar
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 23 days ago
: PD&PEWER Level A&B Postdoctoral - Research Fellow _ CSS.pdf This position will provide opportunities to: Conduct cutting edge research in machine learning, AI and algorithms, such as but not limited
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only within dense, highly interacting systems, inaccessible to standard techniques. To probe such regimes requires the development of fast and scalable algorithms for many-component systems, and of