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constrained and compared, and pre-eruptive tremor will be identified and interpreted. The Scope of Your Responsibilities: Conduct independent code development and testing in Python or similar Separate
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deadline Experience with urban acoustic monitoring or transportation noise assessment Programming skills in Python Knowledge of machine learning techniques applied to acoustic or environmental data
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representation learning. You have strong programming skills, especially in Python, and preferably experience with PyTorch. You have a track record of publishing in top image processing / computer vision journals
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., proficiency in R, Python, ArcGIS) • Knowledge of forest and peatland biodiversity • Fluency in written and spoken English If you are proactive, committed, and efficient, you might be the ideal candidate. You
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expectations of the applicant We are looking for candidates who demonstrate: A solid background in remote sensing Strong computer and software skills, including proficiency in R, Python, and ArcGIS Knowledge
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 15 days ago
https://jobs.inria.fr/public/classic/en/offres/2026-09710 Requirements Skills/Qualifications Profile. We are looking for a candidate with: - M.Sc in Computer Science, Statistics, or related fields
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: RNPUs, Nature 577, 341-345, 2020 . In this PhD project you will work on applying RNPU networks for solving computational problems that are considered hard. Where to apply Website https
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systems (Windows, macOS, Linux). Basic exposure to scripting or query languages (e.g., Python, PowerShell, Bash, or log query languages) sufficient to read or modify existing scripts or queries. Basic
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for 12 months and is available from 1st October 2026. The successful candidate will be based in the School of Mathematics and Statistics at the Open University campus in Milton Keynes. https
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creative disciplines Strong programming skills, Python frameworks for ML and real-time audio software Curating audio datasets, spatial-audio/audio-visual recordings, and ML training/evaluation pipelines