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Algorithm Developer (KTP Associate) ( Job Number: 25001803) Department of Mathematical Sciences Grade 7: - £41,064 - £46,049 per annum Fixed Term - Full Time Contract Duration: 18 months Contracted
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? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The research activity will focus on the development of algorithms for machine
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graduate students, etc. In particular, the MLE hired for this position will work with Ayan Paul and Hyunju Kim at EAI and is expected to develop AI algorithms for drug synergies with a combination of public
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in both instrument and algorithm technologies. The researcher will contribute to the development of the project’s research lines within the macro-themes “Resilience to extremes” and “Sustainable water
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to technical development for mobile and web-based applications, including front-end and back-end support, user-centered app design, implementation of key app features, and integration of algorithms and machine
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-funded AI research group “Fusing Deep Learning and Statistics towards Understanding Structured Biomedical Data (DeSBi)” development of deep neural networks and machine learning algorithms for the analysis
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decentralized machine learning in 6G networks, and design machine-learning algorithms that can handle the network imperfections that remain impractical to resolve at the physical layer. The focus of the research
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 7 days ago
to learning algorithms and targeted applications the integration of various elements enabling data collection and deployment on humanoid robots We are looking for experienced engineers (2+ years) who will be
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to ensure alignment with donor plan. Responsible for comprehensive understanding of HLA donor search algorithms and other non-HLA factors, such as ABO, age and CMV status. Analyze donor searches and apply
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implementing algorithms based on online Sparse Gaussian Processes and advanced probabilistic techniques enabling AUVs to dynamically alter their trajectories, cutting down on uncertainty and improving efficiency