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5 years of relevant work experience as a post-doc and/or in an R&D position, excluding time associated with family planning, military service, illness or other life-changing events. Brookhaven
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the development of high-fidelity finite element models to investigate surface wave propagation in soft biological tissues, forming the foundation for subsequent statistical and machine learning
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of high-fidelity finite element models to investigate surface wave propagation in soft biological tissues, forming the foundation for subsequent statistical and machine learning frameworks that integrate
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join our multi-disciplinary team of researchers, including immunologists, PhD students, physician-scientists, and bioinformaticians. The postdoctoral fellow will work in an NIH-funded laboratory and will
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, Biomedical Informatics or MD with significant concentration in Biomedical informatics, artificial intelligence, data warehousing and machine learning potentially with a MS/M Engineering in the areas above
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findings to military stakeholders and the implementation of evidence-based practices within military medical populations. Therefore, applicants should have experience working with, or significant interest in
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, Biomedical Informatics or MD with significant concentration in Biomedical informatics, artificial intelligence, data warehousing and machine learning potentially with a MS/M Engineering in the areas above
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; • characterization of quantum correlations, entanglement, nonlocality; • machine learning for optimization problems. Website for additional job details https://mfi.ug.edu.pl/strona/112497/konkurs-na-stanowisko-post
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significant mathematical and computational background to learn and develop new AI methods. While demonstrated experience in computer vision and deep learning for pathology or other biomedical image analysis is
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Expertise in machine learning and big data analysis Excellent written and oral communication skills Motivated self-starter with the ability to work independently and to participate creatively in collaborative