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The High Energy Physics Division at Argonne National Laboratory invites applications for a postdoctoral research associate position to conduct research in machine learning (ML) for applications in
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statistical or machine learning methods to complex datasets. Evidence of involvement in grant writing or development of independent research ideas. A commitment to teaching the next generation of researchers
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, Automotive, and Mechanical Engineering, and provides professional education nationally and internationally, supporting lifelong learning. M2 strives for close collaboration between academia, industry, and
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dynamics, quantum mechanical simulations, and machine learning. Proficiency in programming languages and computational software’s. Strong motivation and passion for research in the field of sustainable
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://www.academictransfer.com/en/jobs/355391/postdoctoral-researcher-machine… Requirements Specific Requirements You hold a PhD degree in Computer Science, Data Science, Biomedical Engineering, or a closely related field, with a
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provides professional education nationally and internationally, supporting lifelong learning. M2 strives for close collaboration between academia, industry, and society, focusing strongly on practical
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your help! We have several fully-funded open PhD and Post-Doc positions (m/f) A list of concrete potential projects: Development of modern auto-differentiation (JAX-based) physics simulators
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skills (e.g. Python, Julia) to merge concepts of chemical engineering, operations research and computer science, as you may also need to deploy machine learning to support data analytics and complex
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Université de Bordeaux / University of Bordeaux | Villenave d Ornon, Aquitaine | France | 12 days ago
genomic diversity and genetic load from available genomic data for various woody species. For this, you will use the available pipelines from phase 1 of the project and apply machine learning-based methods
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machine learning analyses will be performed to determine correlations across stimulation settings and body systems as well as to develop predictive models and biomarkers for physiological and clinical