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of Computer and Information Science , within Linköping University . Your work assignments As a PhD student, you devote most of your time to doctoral studies and the research projects of which you are part. Your
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position in biomedical informatics is available at Harvard Medical School to work at the intersection of advanced machine learning and large-scale biomedical data. The selected fellow will join a dynamic
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. You will become part of a dynamic, collaborative working environment with expertise in drilling engineering, geomechanics, machine learning, and energy systems. The project will integrate real‑time
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information, quantum technologies and machine learning. Internal further training & coaching: The Vienna Doctoral School as well as the Department of Human Resources offer plenty of opportunities to grow your
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methodologically strong and motivated to work at the intersection of applied machine learning, social sciences, and natural sciences. Essential qualifications: A completed PhD in data science, computer
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and learning algorithms for structured data. Graphs and networks are ubiquitous in various domains from chem- and bioinformatics to computer vision and social network analysis. Machine learning with
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mental health. The successful candidate will lead analyses of large-scale datasets, applying advanced computational and statistical methods to integrate multimodal data (including MRI, MEG, EEG, and
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of machine learning which clearly integrates the two subject areas within the division. For more information about STIMA, please see https://liu.se/organisation/liu/ida/stima . Linköping University is
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the use of large language models to support neural network design and data preprocessing. The position involves close collaboration with experts in cardiovascular simulation and Scientific Machine Learning
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. Experience with Python programming. Familiarity with machine learning methods. Strong communication skills and ability to work collaboratively across theory and experiment. Desired Qualifications PhD in