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of experience: Data collection or data management Required License No If yes, what is the required licensure/certification? NA Required Computer Applications: Microsoft Excel, Microsoft Word Required Other
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projects as well as third cycle courses, seminars and conferences. You will perform standard physics-based methods to estimate absolute and relative binding free energy. Based on these, you will develop
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guidance, navigation, and control (GNC) systems. The successful candidate will develop and validate Bayesian and non-Gaussian estimation algorithms, data assimilation methods, and tracking frameworks
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 5 days ago
Website https://jobs.inria.fr/public/classic/en/offres/2026-09928 Requirements Skills/Qualifications Profile: - The candidate is completing a Master's or engineering’s degree in Computer Vision, Electrical
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methods, hpc computer programming and mechanics of structures. The candidate's experience and knowledge in the tasks to be performed in the project will be valued at 15%, in particular in numerical methods
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, Microsoft PowerPoint, Microsoft Outlook Required Other Computer Applications: Required Additional Knowledge, Skills and Abilities: 1) Knowledge of the principles and methods of Indigenous education 2
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goals and accreditation standards ; and (iv) conducting quantitative, qualitative, or mixed methods research . Experience can be concurrent. Apply at https://www.join.pitt.edu , #26001790. Please upload
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closely related discipline - At least 1 year experience with human neuroscience research, using behavioral or neuroimaing methods - Current fluency with computer programming (ideally using Python) Candidate
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of advanced modelling and machine learning methods, and may involve the following areas: Dimensionality reduction. Data-driven methods for estimating dynamical models Data-driven methods for estimating
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search will be used to explore combinations. Results: The developed methods are intended to allow the training of balanced but also specialised computer vision models, particularly in the field of face