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experience according to the Institut Pasteur guidelines. Required skills: General microbiology and molecular biology techniques Recommended skills: Genomics techniques (DNA sequencing, RNA-seq, Chip-seq etc
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or equivalent) Experience with sequence or time-series models Bonus: Audio, speech, or music processing Transformers, reinforcement learning, or probabilistic models Interest in brain and behavior Environment You
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Single-cell high-throughput sequencing technologies generate unprecedented volumes of molecular data at cellular resolution, opening new avenues for the application of machine learning
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. If collaborations allow, time and support for an additional personal research project aligned with the team’s research will be encouraged. Environment : The Machine Learning for Integrative Genomics team, led by
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the main bioinformatics software and methods (R, Python, Bash). Knowledge on large-scale genotyping/sequencing data analyses. Good level in statistics. Good level of written and oral English. Ease in a
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Single-cell high-throughput sequencing, extracting huge amounts molecular data from a cell, is creating exciting opportunities for machine learning to address outstanding biological questions
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highly multidisciplinary, looking at infectious diseases through multiple perspectives, multiple scales and multiple data streams. We work closely with a network of collaborators and public health agencies
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organismal properties encoded in the interplay of multiple genes in a network? How does the polymer physics at the level of the DNA affect the identity of a particular cell type? Alternative questions
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multiple processes may be involved, coexisting or even compounding one another. All proposed mechanisms implicate the sensory hair cells of the cochlea. Outer hair cells (OHCs) amplify mechanical vibrations