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to large datasets You have proven programming competence in Python and/or R, and expertise in Linux and high-performance computing environments You have a genuine interest in, and prior exposure (through lab
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experience performing neuroimaging analysis is strongly preferred. Programming: Proficiency in Python is required. Experience working in Linux environment and writing Bash scripts is also expected
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about new methods, is a plus. Strong programming skills in Python or R, and Linux Shell; experience in genomics data processing and open source repositories e.g. GitHub is a plus. Strong motivation and
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solid competency with the standard implementation tools used in autonomous robots and embedded systems (e.g., C, C++, Linux, MATLAB, Python, Robot Operating System, Ardupilot, Solidworks, Gazebo Physics
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experience in analyzing clinical trials data. The applicant must have excellent communication skills (verbal and written), strong programming skills in R with proficiency in UNIX/Linux system. For the meta
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. Experience with Linux/Unix environments, cloud computing, and version control systems (e.g., Git). Additional Information: Responsibilities: Perform comprehensive analyses of microbiome sequencing data (e.g
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. Experience working in a Linux environment preferred. Experience working in high-performance computing environments preferred. Experience working with NCBI dbGaP, TCGA, COSMIC data preferred. Training in
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analysis is a plus. Programming skills in R, Python, SAS, Perl, BASH or similar a plus. Experience working in a Linux environment preferred. Experience working in high-performance computing environments
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and the Linux programming environment. Candidates with background in Physics, Physical Chemistry and Engineering are desirable. Candidates with only prior experience in empirical methods like docking
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achievements in the broader areas of cybersecurity, applied cryptography, and/or hardware security. Experience with Linux and high-performance computing environments. Excellent programming skills in modern