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programming skills in Python and/or R; experience with SQL and Linux/Unix is desirable. • Demonstrated research experience in biomedical informatics, artificial intelligence (AI), machine learning, or data
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proficiency in one or more programming or scientific computing environments, such as Python, R, or MATLAB; A strong publication record appropriate to the candidate’s career stage; The ability to work both
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. Programming experience in a language such as Python or R. Experience working in a cloud environment such as Microsoft Azure. Experience in writing grant proposals and scientific publications. Strong
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Python and experience working in Linux and high-performance-computing environments. Experience developing or using automated and reproducible computational research workflows. Ability to conduct
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sequencing data (e.g., Python, R, or bioinformatics pipelines). Strong record of productivity as evidenced by peer-reviewed publications or preprints. Ability to work both independently and collaboratively in
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models (rodent handling/surgery experience a plus). ● Familiarity with quantitative/computational approaches (e.g., R, Python, image analysis, statistics) is a plus but not required. ● Ability
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analysis software or programming language (R, Python, Stata). Experience in comparative analysis. Ability to integrate into a project-related work team Ability to interact with academic stakeholders in
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-generation sequencing data analysis, including RNA-seq or single-cell RNA-seq. Proficiency in at least one scripting or programming language used in genomics (R, Python, or Bash/Unix). Experience with primary
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including Python and deep learning frameworks. Interest in one or more of the following areas: speech synthesis, music generation, neural audio codecs, diffusion models, audio language models, watermarking
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discipline. They should have strong computational skills, including experience with UNIX/Linux and programming in Fortran, Python, or other high-level languages. Candidates should also demonstrate the ability