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pipelines in Python and R. Perform experiments in cell culture and animal models to validate the findings. Coordinate the collaboration between the chronobiology lab (led by Dr. Paul Petrus) and the
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ability to handle large and complex datasets, including preprocessing and integration. Strong programming skills (e.g., Python, R, MATLAB, or similar). Demonstrated ability to conduct independent research
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cells and bioinformatic analysis Strong programming skills (e.g., R and Seurat) Merits: Particularly meritorious is experience in analyzing single-cell data from blood cancers and strong knowledge
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programming in R, Python, and mathematics/statistics. The main duties involved in a post-doctoral position is to conduct research. Teaching may also be included, but up to no more than 20% of working hours
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. The candidate is expected to have a solid grounding in programming in R, Python, and mathematics/statistics. The main duties involved in a post-doctoral position is to conduct research. Teaching may
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ability to comfortable processing these data using tools like Seurat, Scanpy, or QuPath. Proficiency in Python or R, coupled with familiarity with machinelearning frameworks (e.g., scikit‑learn, PyTorch
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R&D&I projects, while RAI was also participating in the DARPA SUB-T challenge with the CoSTAR Team lead by NASA/JPL (https://costar.jpl.nasa.gov/ ). Subject description Robotics and artificial
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in mouse models and cell cultures. Analyze and interpret omics data using bioinformatic pipelines in Python and R. Perform experiments in cell culture and animal models to validate the findings
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working knowledge analyzing forests, for example ecosystem growth rates, or population genetic structure. The post doc must be well versed in data analysis in R, including univariate and multivariate
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fluid dynamics and vascular modeling in microenvironments Skills in data analysis and image processing (e.g., Python, R, ImageJ) Ability to mentor junior researchers and contribute to team leadership What