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skills in R and/or Python and experience in statistical modelling of high-dimensional biological data. Experience working in HPC environments and managing large-scale sequencing datasets is essential
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experience working with large, complex data from varied sources. The candidate should have proficiency with statistical software, ideally Stata, strong written and interpersonal communication skills, and a
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. The position requires experience with at least one of the following: Data Science, Machine Learning, Computational Social Science, Big Data. Relevant skills could include statistical analysis, data management
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from Physical Review Letters. Some of our works are highlighted by globally prestigious journals including Nature. More information, please refer to our website. This will be a great opportunity to join
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one or more of the following areas is a BIG PLUS: data science (machine learning and AI), cancer biology, animal physiology, organic chemistry, E3-ubiquitin biology, and gene editing. In all cases
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disease, including AI-powered tools and new statistical techniques that leverage large datasets, heavy computational capabilities, and/or a robust understanding of biological systems to provide unique
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Aarhus University is seeking three postdoctoral fellows for research on metabolic dynamics and pl...
environment of large scale syngas fermentation. The approaches include, but are not limited to, building reactor platforms for studying adaptive evolution, operating long-term adaptive evolution experiments
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primary research areas: 1) statistical inference in high-dimensional and large-scale testing scenarios; 2) the development of novel model architectures for large-scale proteomics data; and 3) causal
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biology, epigenetics, pediatric solid tumor, and working with patient samples and large datasets is required. The ability to work both independently and collaboratively is also essential. Must be computer
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(circRNAs) are associated with Alzheimer’s disease status and when measuring in blood can be used as disease biomarkers. We have generated brain and blood transcriptomic data in thousands of samples with