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and statistical skills, with proficiency in R or Python Experience working with longitudinal data, infectious disease epidemiology, or high-dimensional datasets Demonstrated track record of peer
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Strong analytical, research, and scientific writing skills Proficiency in Python for modeling and machine learning applications Effective communication, teamwork, and presentation abilities Self-motivated
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, presentations, and draft manuscripts. Proficiency in hard skills, such as implementing and evaluating algorithms in Python, and maintaining reproducible experimentation. Competent in soft skills, such as problem
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Strong planning, organizational and analytical skills Excellent communication skills, both written and verbal Proficiency in programming languages (Python, R, or bash) Be familiar with single-cell RNA-seq
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languages such as Python, R, Matlab (preferably Python). Ability to learn new tools and content quickly and independently. Strong communication skills. The hourly pay range for this position is from $27.01
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Mathematics, or similar) Experience in energy modeling, optimization, or advanced algorithms Programming skills (Python, Matlab, or similar) Spanish and English required What We Offer High-impact national
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, supervise BSc and MSc theses, and contribute to high-quality education. We seek candidates with strong teaching skills and programming experience in R, Python, and/or STATA, who are eager to inspire students
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 3 days ago
publication record in biomolecular modeling and computational biophysics/chemistry. Programming skills (e.g., bash scripting, python, Fortran, C++ and CUDA), expertise in computational modeling (such as
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algorithms Python and relevant libraries (e.g., PyQt, OpenCV, NumPy, scikit-learn), particularly for developing Windows desktop application software incorporating deep learning models Hold at least a
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., using Python and/or MATLAB). Ability to work effectively in an interdisciplinary team and communicate clearly across disciplines. Experience handling large datasets and using reproducible analysis