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for a postdoctoral position in plant cell wall dynamics and mechanochemical signalling. The expected starting date is September 2026 or according to agreement. Umeå Plant Science Centre (UPSC) is one
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measurements. Have a background in computational biology, bioinformatics, or machine learning for biological problems. Have experience with modern deep learning frameworks (PyTorch, JAX, or equivalent). Have
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on development of novel computational methods with state-of-the-art machine learning for gaining fundamental insights into healthy and diseased human tissues of the heart, cardiovascular system, and
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aims to explore to which extent machine learning methods can help with these tasks, e.g. object reconstruction and signal/background discrimination. This will be a focus in the project. One exciting
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methods that combine soundscape targets, acoustic metamaterials, physical modelling, inverse design, machine learning and perceptual evaluation. The postdoc will develop models and design methods
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. Required qualifications: PhD in a field such as physics, systems biology, applied mathematics, machine learning, or related fields. Strong programming skills (e.g. Python) and experience with modern ML
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, Cybersecurity, AI, Machine Learning (ML), Data Science, or another closely related subject, no more than three years before the application deadline; has documented knowledge of AI and ML; has demonstrated
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. Python, Julia, C++, R); experience with sequencing (NGS) data, geometry or graph algorithms, statistical inference or machine learning; error-correcting codes or information theory; molecular modelling
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. The following experience will strengthen your application: industrial product development or manufacturing research modelling and simulation, digital twins or digital threads AI, machine learning
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description Work on EU projects to develop next‑generation transport, emission and health forecasting models by integrating deep learning, xAI, and diverse data sources such as traffic sensors, smart‑card data