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(http://vanallenlab.dana-farber.org/) to work on the analysis of new datasets generated in the context of multiple clinically oriented cancer sequencing projects in order help advance efforts
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associate to carry out research on machine spatial reasoning. The appointment is for one year, renewable for a second year, given the availability of funds. The focus is on developing tools for characterizing
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statistical and machine learning methodologies to analyze and predict aspects of the collected data With the guidance of Drs. Stuber and Bruchas, develop experimental methodologies related to two-photon imaging
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%): Participating actively in training sessions, workshops, and conferences to stay current in the research field Enhancing technical skills through continuous learning of new methodologies, software, or statistical
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or treatment of Alzheimer’s disease. Position Lead and conduct the processing and statistical analysis of large-scale long-read RNA and DNA sequencing, single nuclei RNA sequencing and spatial transcriptomics
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in spatial analyses Excellent scientific writing skills, including ability to lead high quality multiple-authored journal papers in an efficient manner Strong ability to work independently and to
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and philosophers, including one other PhD student (statistics) and two postdocs (spatial forest ecology and philosophy/social science). The candidate is expected to contribute toward developing
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University of California, San Francisco | San Francisco, California | United States | about 1 month ago
biological or other research data. Utilizes and develops algorithms, computational techniques, and statistical methodologies. Helps in the design of new experiments. Implements end-user needs in database
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: Analysis and interpretation of high-resolution single-cell RNA-seq and scATAC-seq data to elucidate cellular processes Processing and integration of spatial transcriptomics data to reveal molecular patterns
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emission') et des corrélations spatiales inexpliquées entre des points d'émission distants. Dans ce contexte, une approche moléculaire est complémentaire aux barrières d'oxydes métalliques largement étudiées