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to detail and follow through. 3. Demonstrated proficiency with MS Outlook, Excel and Word and to work with and learn various types of computer software programs. Technologically savvy with a well-developed
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language processing, machine learning and skills taxonomies, you will help generate meaningful insights into current and future engineering skills needs. Your work will support industry, policymakers, educators and
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, embracing failure as a learning opportunity, and continuously enhancing our knowledge and methods to tackle local, national, and global challenges. The postdoctoral associate will work directly with both
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to an advanced Laboratory Directed Research and Development (LDRD) project, "Machine Learning Steered EXAFS Fitting for Autonomous XAS Analysis," aimed at revolutionizing real-time analysis of X-ray Absorption
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: 10.1101/2025.09.08.674950), and AI/machine learning. We work closely with clinicians to translate our findings into clinical practice, focusing on genomically complex sarcomas and haematological
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: Learn more about the innovative work led by Dr. William Shih here: https://www.shih.hms.harvard.edu/ . What you’ll do: Design nucleic-acid nanostructures and assemble them in a wet laboratory
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thereafter. You are stimulated to apply for a personal postdoctoral funding. The position is immediately available. (Early) access to state-of-the-art as well as novel machine learning infrastructure and
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at: https://www.umu.se/en/department-of-computing-science/ Project description and working tasks The project will develop privacy-aware machine learning (ML) models. We are interested in data driven models
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combine density functional theory (DFT), molecular simulations, and machine-learning force field (ML-FF) development to uncover the factors controlling NHC–surface interactions and to model realistic
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and application of AI and machine learning methods; (iii) a good track record of research and publication in top peer-reviewed scientific journals in the area of general medicine, cardio