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Department/Location: Department of Genetics Applications are invited for a Postdoctoral Research Associate position to work in the group of Dr Felipe Karam Teixeira (https://www.gen.cam.ac.uk
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between various imaging modalities and multi-omics during aging and development. • Implementing computationally intensive algorithms on high-performance computational clusters
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well as genetic and non-genetic sources of inter-individual molecular variation, with the ultimate goal of better understanding human biology and disease. We will achieve these goals by developing novel and
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), National Animal Disease Center, Virus and Prion Research Unit, located in Ames, Iowa. For an introduction to the flu-crew at the National Animal Disease Center, please see: https://youtu.be/kOJy8tFTuiI
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-based tiles can be arranged and actuated to form tunable metapixels, enabling dynamic control of light at the nanoscale. This project will integrate algorithmic self-assembly and nanomechanical switching
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or equivalent research experience in bioinformatics, computational biology or related subjects; should be familiar with state-of-the-art NGS tools, algorithms and pipelines for processing and
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/tools or machine learning algorithms. Good computer programming skills in R/Matlab/PerlPython. Knowledge of basic molecular biology, genomics, and epigenetics. Experience in next-generation sequencing
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biology due to significant species-specific differences in neutrophil biology. For example, human neutrophils contain antimicrobial proteins that are absent in mouse neutrophils. Reliance on mouse models
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Is the Job related to staff position within a Research Infrastructure? No Offer Description The researcher will use and further develop ptychography algorithms for transmission electron microscopy data
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Inria, the French national research institute for the digital sciences | Bron, Rhone Alpes | France | about 1 month ago
. Test model predictions in behavioral experiments. Investigate how principles of biological adaptability can inform the design of efficient and robust learning algorithms for artificial systems