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including spectral flow cytometry, machine learning and irradiation techniques to generate bone marrow chimera models. Utilize mouse models and patient-derived samples to explore how biological immune aging
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role in designing composites materials using inorganic solid electrolytes using computational modelling and machine learning. Qualifications • Ph.D. in Materials Science, Chemistry, Physics, or a
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protein foods including through high moisture extrusion. Key responsibilities will include: Explore innovative methods for food process optimization including the use of AI and machine-learning Develop and
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machine learning methods for computational materials physics and chemistry. Projects include: The aim is to develop generalized equivariant neural network models NequIP and Allegro for machine learned
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in empirical analysis using econometric, machine-learning, and language-modeling techniques. Conducting literature reviews and synthesizing existing academic research to support ongoing projects
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qualifications will strengthen the application: Experience with AI or machine learning applied to environmental systems Experience with coastal circulation modelling tools (e.g., Delft3D, MIKE, ROMS, FVCOM
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experience) in applied mathematics, physics or engineering, and strong, up-to-date specialist knowledge in analytical and numerical spray modelling and machine learning. Experience with OpenFOAM or similar CFD
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and Machine Learning, with a focus on studying geometric structures in data and models and how to leverage such structure for the design of efficient machine learning algorithms with provable guarantees
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will focus on developing efficient foundation models to medical image analysis. Foundation models offer a scalable and adaptable solution for medical image analysis by learning generalizable
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Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial | Portugal | 12 days ago
). Experience in machine learning methods, including data preprocessing, model selection, and performance evaluation. Familiarity with programming languages commonly used in these domains (e.g., Python, MATLAB