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, Statistics, Genetics, Computer Science, or a related field. Excellent communications skills in English (both verbal and written). Proficiency in using R/Bioconductor and Perl/Python for genomic data analysis
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thinking skills. Competence in data analysis and visualization using software such as GraphPad Prism, R, or Python. Excellent scientific writing and communication skills, with a track record of peer-reviewed
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for scientific presentations using Power Point, R/Python and other graphics software as needed. Search literature for references to technical problems and keep informed by reading technical journal and
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score derivation and validation, and other relevant analyses. Develops R or Python scripts for data analysis, statistical modeling, and machine learning techniques, ensuring reproducibility and efficiency
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projects. Experience with grant writing, mentoring students, and collaborative academic or industry research is preferred. Knowledge, Skills and Attitudes: Strong programming skills (Python, C++, MATLAB) and
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analysis, basic scripting in R or Python, and integration of multi-omic datasets is considered an advantage. Candidates should also possess a strong publication record in high-impact journals and a
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such as glaucoma, macular degeneration, and uveitis. Programming in Python and R languages with knowledge of Google Tensorflow, PyTorch, scikit-learn, and Keras or other related deep learning libraries
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ethical frameworks. Proficiency in Python and experience with relevant libraries for AI/ML development. Experience with advanced AI methodologies including deep learning, transfer learning, and neural
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with Matlab, Python, and/or R programming languages is a plus. Knowledge, Skills and Attitudes: Skill in collecting, organizing, and analyzing data. Analysis of fMRI and MR spectroscopy data Acquiring
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languages such as Python, MATLAB, or C++, and experience with machine learning frameworks (e.g., TensorFlow, PyTorch) preferred. Familiarity with medical imaging processing and reconstruction techniques