245 parallel-computing-numerical-methods Postdoctoral research jobs at Nature Careers
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with skills in computation and image processing is highly desired. Excellent communication skills and an ability to work across platforms in a collaborative style are desired. St. Jude is an Equal
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As a fellow you will join our faculty in the Department of Biostatistics, providing statistical support and developing innovative biostatistical methods for research projects at the cutting edge
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considered an asset Training and experience in quantitative empirical methods Good command of multivariate and complex statistical methods International publications in peer-reviewed journals and / or book
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(FSTM) at the University of Luxembourg contributes multidisciplinary expertise in the fields of Mathematics, Physics, Engineering, Computer Science, Life Sciences and Medicine. Through its dual mission
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environment in the fields of science, technology and administration as well as for the education of highly qualified young scientists. The computational imaging group at DESY is concerned with the development
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extensive cell tracking studies with massive parallel sequencing and molecular manipulations to gain insights into regulatory mechanisms whose appropriate targeting could impose regenerative traits to mammals
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consortium SynThera funded by the Carl Zeiss Foundation (www.synthera.eu/ ). We are seeking an excellent and enthusiastic post-doctoral researcher with a strong interest in computational microbiome research
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, or similar disciplines Graduate students expecting to receive their PhD within six months can also apply Experience in the advanced analysis of genetic or proteomic data Interest in learning methods
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experimental and numerical approaches. Materials classes of interest include components (monomers, polymers, additives, (nano)particles, etc.) utilized in high-performance polymeric materials with relevance in
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Nature Careers | Vancouver South Shaughnessy NW Oakridge NE Kerrisdale SE Arbutus Ridge, British Columbia | Canada | 28 days ago
, mathematics, and data science. Collaborative projects merge traditional geographic research with advanced computational methods such as graph neural networks (GNNs) and large language models (LLMs) to explore