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great advantage: Forest and wood production processes Wood construction Furniture manufacturing Wood material science Machine learning Process simulation and optimisation The postdoctoral fellow is part
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physics, applied mathematics, machine learning, bioinformatics, biophysics, spectroscopy, image processing, ecological modeling, molecular biology, plant physiology, marine biology or an interest in gaining
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-ray Science. AMBER is funded by the EU Marie Skłodowska-Curie (MSCA) COFUND scheme. Around 20 postdocs will be recruited in the fourth call 2025, with each fellowship lasting 36 months. AMBER has six
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Injection Systems (CIS) — natural protein machines used by bacteria to deliver molecular cargo. The group's mission is to understand the structure, function, and application of CIS for use in both
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passive and active flow control algorithms, potentially incorporating machine learning/AI, to enhance aerodynamic performance and stall delay with rapid response times. The research is conducted in
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, computational materials science, computer science, or a related field, awarded no more than three years prior to the application deadline*. Background in physics-based battery modelling and/or machine learning is
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application! Work assignments Subject area: Computational studies of the influence of microstructural features on the structural integrity of metallic materials using machine learning Subject area description
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service. Contract terms This postdoc position is a full-time temporary employment for two years with the possibility of a one-year extension. We offer Chalmers offers a cultivating and inspiring working
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environment project, we will develop automated species and community recognition, particularly focusing on pathogenic soil fungi, with help of deep-learning algorithms fed with microscopic image and Raman
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X-ray Science. AMBER is funded by the EU Marie Skodowska-Curie (MSCA) COFUND scheme. Around 20 postdocs will be recruited in the fourth call, with each fellowship lasting 36 months. AMBER has six core