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Field
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Degree is required Major in Neuroscience is preferred Experience of working in a Neuroscience Laboratory preferred Experience with software programs such as excel, SSPS, and matlab preferred Experience
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. Required: * Experience using Linux/Unix systems required. * Experience using scripting languages such as Python and Matlab. * Familiarity with relational databases and SQL required. Preferred: * Familiarity
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., R, Matlab, SPSS, Primer or Python) Experience with data analysis techniques (e.g., ANOVA, PCA, Regression, MDNS) Experience with ecosystem service identification and analysis Excellent data management
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or MATLAB). Preferred Qualifications Hardware-software integration and embedded control. Field deployment experience in harsh or remote environments. Collaboration with earth science or seismology teams. Good
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to modeling. Understand, integrate, and use widely accepted as well as novel approaches to pharmacometric modeling and statistical analysis (e.g., R, Matlab). Utilize routine pharmacometric software (e.g
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electrophysiology in rodents and Matlab/Python-based data analysis. Applicants must have a Ph.D. or equivalent degree. Responsibilities may include working independently and as part of collaborative research groups
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the following courses: ENED 1020 ? Foundations of Engineering (a laboratory course that serves to introduce students to all the fields of engineering) ENED 1090 ? Engineering Models I (a MATLAB focused
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; Domain knowledge in ATM is highly advantageous. Strong research contributions, evidenced by publications in SCI Q1 journals and peer-reviewed conferences. Proficiency in programming (Python, C++, MATLAB
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equivalent) Strong programming experience (C++, Python, Bash, Matlab; min. 3 years) Experience with Linux systems and/or Robot Operating System (ROS) Knowledge of object-oriented design, multithreaded
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.). Fluency in programming languages such as Python, R, Matlab, Perl; MySQL. Experience working with UNIX/Linux environment. Experience in nucleic acid isolation and sequencing library preparation. Familiarity