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Field
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analysis of high-dimensional data (e.g., single-cell RNA-seq, phylogenetics, spatial data). Experience in R or Python. Application instructions: Please send a CV and a brief cover letter describing your
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preferred. Experience with atmospheric models (e.g., GEOS-Chem, CMAQ) and skills in python, Fortran and high-performance computing are also desired. Position Status Full Time Posting Number 25FA0918 Posting
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applying machine learning or other elements of artificial intelligence to solving significant scientific or engineering problems Interest in software development, with particular emphasis on the Python
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performance for data throughput and latency Extend functionality to interact with Python or REST APIs Interface with collaboration partners and participate actively in a collaborative work environment to turn
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in MATLAB/Python/R are desirable but not required. The position is part of a well-funded research program and will provide the opportunity to produce high-impact publications and establish
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, biostatistics, biomedical informatics or related fields OR a PhD degree in biology or related fields. Preferred Qualifications: A strong background in programming (e.g., Python or R or C++) is essential. Research
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at time of start) PhD or equivalent international degree. Preferred qualifications PhD in physics or astrophysics field. Strong programming skills (e.g., Python) for scientific computing and simulation
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experience with spatiotemporal analysis using R, Python, and/or comparable computer programming languages. Presenting results at national conferences. Leading the development of manuscripts with the aim
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written and oral communication skills. Experience with MPI, OpenMP, parallel I/O (including HDF5), CUDA and/or OpenACC, Fortran, C++, Python. Motivated self-starter with the ability to work independently
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decision support systems. The candidate would also assist in writing python/R programming scripts to optimize processing time, making the current decision support systems more efficient and reliable