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application! We are looking for a PhD student for sustainable and resource-efficient machine learning. Your work assignments Machine learning has recently advanced through scaling model sizes, training budgets
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an increased interest in adapting and developing the latest machine learning methods for the purpose of malware detection, and preliminary results are encouraging. The specific goals of this project include
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services can be found at: https://www.uu.se/forskning/snpseq and https://ngisweden.scilifelab.se/ We are proud to deliver high-quality data and are accredited by SWEDAC as a testing laboratory under the ISO
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position as Senior Lecturer. Optimization, machine learning, and control theory together form a central toolbox for understanding, analyzing, and controlling complex systems. These fields span deep
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, incorporating their own ideas and experience in computer vision, machine learning, and related fields, to further visualization and interpretation of molecular images. Our research environment focuses
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data (HRMS) used for non-target analysis. The projects aims to develop a combination of supervised and unsupervise machine learning stragaties for pinpointing chemicals that have high toxicity
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are looking for a postdoctoral researcher with a strong background in speech synthesis and machine learning, with an interest in accessibility and human communication. Your Role You will: Plan and lead
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quantitative or computational approaches are required. Prior experience with image analysis, machine learning, signal processing, or structural biology is meritorious but not mandatory. Excellent written and
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practical skills in the field of data science, especially. multimodal data analysis. Experience on image processing (especially on MRI data) via machine learning. Programming skills (e.g., Python
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%). You will work at the intersection of numerical analysis, uncertainty quantification, and scientific machine learning. The research will primarily focus on probabilistic methods for data-driven model