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* Experience in one or more of: AAV/vector biology, in vivo gene delivery, mouse models/surgery, single-cell/spatial transcriptomics, ATAC-seq, microscopy, quantitative imaging, computational analysis (R/Python
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programming expertise in at least one of the C++, C# and Python languages. Background Investigation Statement: Prior to hiring, the final candidate(s) must successfully pass a pre-employment background
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• Computational skills for multi-omic data analysis (R, Python) is a plus. Department Contact for Questions Dr. Asmaa El-Kenawi Email: asmaa.elkenawi@cancerimmunometabolism.com Website: https
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Python, R, or MATLAB. Knowledge of systems biology and integrative approaches to studying microbial communities. Experience in mentoring and teaching Qualifications: A Ph.D. in Computational Science
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researching the auditory midbrain (inferior colliculus). Detail-oriented, quantitative mindset and experience with scientific programming (Matlab, python, or R) is critical. Strong organizational, leadership
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, ICLR, ICCV, NeurIPS, AAAI, ECCV, MICCAI, IPMI, ICRA, IROS, RSS, and associated journals) Demonstrated ability to independently lead research projects Expertise with Python and relevant libraries (e.g
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Center for Drug Evaluation and Research (CDER) | Silver Spring, Maryland | United States | 9 days ago
evaluation of the AI prototype by assisting with basic data tasks: you will help organize test data and run pre-written Python scripts to generate performance metrics. This will provide you with introductory
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Center for Devices and Radiological Health (CDRH) | Silver Spring, Maryland | United States | 9 days ago
., Python, g-code) Data analysis Statistical analyses How to create reports Mentor: The mentor for this opportunity is Prasanna Hariharan (Prasanna.Hariharan@fda.hhs.gov ). If you have questions about the
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in research methods or data analysis Proficiency with data analytic programs (e.g., Stata, SPSS, AMOS, SAS, R/Python, etc.) Experience translating and disseminating research findings to broader
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reporting standards * Familiarity with deep learning technologies (e.g., CNNs, transformers) * Experience with Python and ML ecosystem skills (e.g., PyTorch, scikit-learn, etc.). * Skilled in writing and able