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analytical research on cell-type specific human brain development, and neurological diseases. The project will involve bioinformatic analyses of large datasets with Python and R programming languages. It is
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, completed prior to the start date; Experience working with the scientific Python ecosystem (NumPy, SciPy, Matplotlib, etc.) and with databases (SQL, etc); Experience with collaborative version control systems
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automation (Python preferred). • Ability to interface experimental physics with electronic hardware systems. Website for additional job details https://emploi.cnrs.fr/Offres/CDD/UPR2940-LEIMOG-007/Default.aspx
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. Internationally recognized for the excellence of its scientific research, the CNRS is a reference in the world of research and development, as well as for the general public. Where to apply Website https
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analysis (16S rRNA sequencing, QIIME2, DADA2, R/Python) and experience with rodent models of inflammation or dietary intervention studies. Applicants should be highly motivated and creative, have excellent
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appointment. Appointment Start Date: The start date is flexible. We will review applications on a rolling basis. Group or Departmental Website: https://pathology.stanford.edu/(link is external) How to Submit
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journals. You have experience setting up quantitative research and can readily program experiments. You have strong statistical skills and can work with scripts, for example in R or Python/Matlab. You have a
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in one of the following areas: Machine Learning / Information Retrieval / Knowledge Graph Representation / Recommender Systems Graph Theory/Network Science Python, and up-to-date machine learning
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language at the ESRF) Preferred Qualifications: Knowledge of scientific programming (preferably Python). Experience with instrumentation relevant to high-energy X-ray diffraction beamlines Working conditions
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experimental control and scientific data analysis, preferably using Python, C/C++, MATLAB, LabVIEW or related tools The ability to guide junior researchers and coordinate work across a collaborative experimental