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Field
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, COMSOL, or similar). • Programming and data analysis skills (MATLAB, Python, etc.). • Strong communication skills and ability to work in a team-oriented environment. Preferred
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chromatography and liquid-liquid extraction Experience with automated control systems. Familiarity with Aspen Plus software, Python, thermodynamics, and general chemical purification techniques. Familiarity with
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Proficiency in R or Python Minimum of two years of experience in computational biology or cancer genomics Experience with high-performance or cloud computing (e.g., HPC, AWS, GCP) At least one first-author peer
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. Solid skills in at least one programming language (R, Python, or Perl) and experience working in Linux and/or high-performance cluster environments. A strong ability to perform analytical reasoning
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genomics approaches. Familiarity with computational analysis (e.g., Python, R, Bash) and/or genome-scale data integration. Experience with cell culture and functional genomics (e.g., CRISPR/Cas9), cancer
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Qualifications – Experience, Education, Knowledge & Skills Data Science Experience: Proficiency in using R or Python for phylogenetic comparative methods and high-performance computing (HPC) environments
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in programming, ideally with experience in languages commonly used in computational biology (e.g. Python, C). Experience with HPC, workflow managers (e.g. Snakemake, Nextflow), and containerization
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, engineering, or related field Comprehensive experience programming in one or more programming languages such as Python, C/C++ Experience with at least of one of the AI frameworks is required, such as PyTorch
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for reporting tools, experience using AI in data analysis, proficiency in dashboard creation with platforms such as Tableau or Power BI, and programming experience with R and Python. The ideal candidate will have
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Longitudinal neuroimaging analysis Programming in Python, R, and/or MATLAB Reproducible research practices and Git-based version control Preferred technical depth Neuroimaging software: FSL, FreeSurfer, ANTs