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Field
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). Information Key Responsibilities: Develop a generalizable and explainable (gray-box) model for adaptive patient monitoring. Utilize a mixed approach combining real and synthetic data for algorithm development
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into learning architectures. Collaborating with experimental research groups, enabling real-world validation and application of newly developed algorithms.
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The Department of Mathematics and Computer Science (IMADA) at the University of Southern Denmark, Odense, invites applications for a PhD position in algorithms. The position has a duration of 3
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: Developing innovative methods from the field of machine learning for biomedical data, e.g., explainability, interpretability, and causal inference Contributing to the design of novel algorithms and models
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group of the University of A Coruña. The hired person must collaborate in the application of techniques based on computational grammars to the development of green natural language processing algorithms
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(Edge AI) enables deploying AI algorithms and models directly on edge devices. However, AI workloads demand high performance processing, large scale data handling, and specialized hardware accelerators
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Contribute to the development of new algorithms and methods for the efficient analysis of large-scale omics datasets Participate in workflow automation and management using systems such as Snakemake
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Inria, the French national research institute for the digital sciences | Pau, Aquitaine | France | 6 days ago
science as part of the ERC Starting Grant project Incorwave, which aims to develop advanced numerical and mathematical methods for passive seismic imaging. The research will focus on two key-directions: (1
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algorithms for microscopy image analysis problems (primarily 2D timelapse data), which are driven by real applications in life science research Develop solutions to integrate large foundation models
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The Medicines And Healthcare Products Regulatory Agency; | Canary Wharf, England | United Kingdom | 4 days ago
services. Responsibilities include leadership of commissioned research; characterising, validating, and integrating new sources of data; monitoring data quality; developing methodologies and algorithms