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Research Center for Molecular Medicine (CeMM), ÖAW | Vienna, Virginia | United States | 2 months ago
on LazySlide ( et al Nature Methods ), our scalable software foundation, and our deep learning framework for age prediction (Abila et al., Nature Medicine, in press) to engineer a body-scale machine learning
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years of experience post receiving their PhD). A strong preference is for individuals with (a) computer science or computer engineering degrees with previous experience in natural language processing
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systems, from the physical fabrication of flexible printed circuit boards (FPCBs) to the implementation of machine learning algorithms for real-time signal analysis. The postdoc will collaborate in a
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the theory of brain-inspired algorithms and apply them to complex, real-world problems. The successful candidate will join an interdisciplinary team of computer scientists, mathematicians, engineers, and
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publish research findings in peer-reviewed high-impact journals. Required Qualifications A postdoctoral research associate requires a PhD in Electrical Engineering, Physics, Materials Science and
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science, machine learning or a related field. Strong experience working with clinical, biomedical, genetic, electronic health record, or health administrative data. Experience with large language models
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Qualifications: A PhD, MD/PhD, or equivalent research doctoral degree in neuroscience, biomedical data science, computer science, psychology, psychiatry, statistics, engineering, applied mathematics, or a related
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to evolving technical challenges • Perform other duties as assigned in support of overall project goals Required Qualifications and Skills • PhD in Biomedical Engineering, Mechanical Engineering
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Science Research unit: https://genomics.iit.it/ ESSENTIAL REQUIREMENTS PhD in computational biology, machine learning, bioinformatics, physics or related fields; High proficiency level in programming
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publish research findings in peer-reviewed high-impact journals. Required Qualifications A postdoctoral research associate requires a PhD degree in Electrical Engineering, Physics, Materials Science and