53 parallel-programming-"Multiple"-"Humboldt-Stiftung-Foundation" Postdoctoral positions at Nature Careers in United States
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with cutting-edge technology, accelerates research productivity. Customized Professional and Career Growth: Experience specifically designed programs to enhance professional growth and career readiness
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, physics, mathematics, computer science, or related fields Demonstrated hands-on experience with machine learning techniques Strong programming skills (Python preferred) Experience analyzing time-series data
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programs that control stem cell development, and how these processes go awry in cancer progression. Our lab is equipped with cutting-edge metabolomics, genomics, molecular biology, and bioinformatics
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' datasets - genomics transcriptomics, and proteomics Proficiency in R, Python, and other programming languages Expertise in Linux, Git, Docker, and other high-performance computing environments Excellent
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Program dataset, and also make use of many other datasets, including our own Yale-Penn sample, Thai sample, and other samples, as well as the UK Biobank, AllOfUs, etc; (b) Psychiatric Genomics Consortium
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led by expert scientists and equipped with cutting-edge equipment. Customized Professional and Career Growth: Experience specifically designed programs to enhance professional growth and career
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Postdoctoral researcher (f_m_x) - Waves in the Inner-magnetosphere and their Effects on Radiation...
satellite data processing and numerical simulations. Responsibilities will include a variety of tasks related to numerical simulations and scientific programming. These will include, but are not limited
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that can be used by engineers. Your responsibilities: Maintain data and code repositories Develop real-time visualisation on the website Develop various programming tools for scientific codes and data
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programming languages (e.g., R, Python). Successful applicants should be self-motivated, well-organized, and able to work independently and collaboratively. Excellent written and oral communication skills
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with experience in One Health or climate-health research. Proficiency in systematic reviews, survey methods, and/or causal inference is essential, along with programming skills (e.g., in R or Python