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basis, eventually renewable but never exceeding the end of the project. If it is not possible to ensure the duration of 5 months estimated in the previous paragraph, this duration will be adjusted
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in Computational Electromagnetics will be responsible for developing theoretical models and high-performance computer codes for modelling the interaction between electromagnetic waves and dielectric
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the computational neuroimaging group (https://conilab.nottingham.ac.uk ). The team have an established track record in developing computational neuroimaging technologies for mapping the brain at a
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. The project focuses on resilient control and estimation methods for electrified vehicles, with particular emphasis on safety, comfort, fault tolerance, and battery aging. Electrified vehicles are a key
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to scientific computing and other scientific domains. Candidates with strong backgrounds in stochastic analysis, numerical analysis, sampling methods, optimization, scientific computing, or related areas
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Level 06 Salary Range $16.20-24.82/hour Type of Position Staff Position Time Status Full-Time Required Education HS Click here for more information about equivalencies: https://hr.uky.edu/employment
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 2 months ago
- SIPG LAB/ISR and 1801P.01460.1.04 LARSYS/ISR BASE 2025-2029 – SIPG LAB/ISR, financed by national funds through FCT/MCTES Workplan: Develop new representations for computer vision and machine learning
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The Ho Lab at Yale University School of Medicine (https://medicine.yale.edu/lab/yachiho/ ) is recruiting motivated, productive, independent, and collegial postdocs interested in viral infection, T
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meaningful methods that can translate beyond narrow benchmark settings. The successful candidate will work closely with the Project Lead and partner clinical collaborators to develop and evaluate AI methods
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Dipartimento di Ingegneria dell'Informazione - Università degli studi di Padova | Italy | 2 months ago
will design and implement federated learning methods for heterogeneous multimodal biomedical data with a specific focus on data quality assessment and quality-aware model training. Within the HEREDITARY