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information about the network: https://euraxess.ec.europa.eu/jobs/401249 1. Context and Challenges Title: Physics-Informed Neural Operators (PINO) for Ultra-Fast Tomography: Toward Fundamental and Generalizable
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. Through continuous structural monitoring systems Through continuous structural monitoring systems and artificial intelligence algorithms (machine and deep learning, hybrid physical-data driven methods
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for fast tune-up Implementation and benchmarking of quantum algorithms Qualifications We are seeking candidates with: A PhD in Physics, Applied Physics, Nanotechnology, Computer Science, Engineering, or a
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reliable models and algorithms in these contexts (weakly supervised, semi- or unsupervised learning, domain generalization, active learning, federated learning, privacy preservation, noise and uncertainty
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 2 months ago
to responsible AI. Starting Date. Flexible start in early 2026. Selected references. - [1] Dwork, Cynthia, and Aaron Roth. "The algorithmic foundations of differential privacy." Foundations and Trends® in
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are filled. An earned doctorate is required by the start of the appointment, and a background check must be completed prior to beginning employment. Application materials should be submitted to http
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. Application materials should be submitted to https://www.mathjobs.org/ . The Georgia Tech official website for applications is https://hr.gatech.edu/careers . Some candidates who do not apply there at first
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the project’s deliverables. 2. To perform internationally competitive research in the analysis of transcriptomic and epigenetic data. 3. To provide analytical and statistical expertise, and algorithms for data
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on the development of algorithms for ECG signal analysis and validation of novel biodegradable ECG electrodes. The contract will be within the framework of the “Green Electrodes for Sustainable Electrophysiology
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using LLMs in therapeutic settings: data confidentiality, algorithmic biases, and limitations in contextual understanding. Study the acceptance of these tools by both patients and healthcare professionals