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data analysis and development of evaluation methods (e.g., in Python) Support in conducting experiments in the laboratory What you bring to the table Current studies in engineering, materials science
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: Python (Django), Java (Spring), TypeScript (React), Docker, Terraform, GCP. We maintain a DevOps culture and use Scrum for our day to day work. We have also adopted an "open by default" approach to new
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Lawrence Berkeley National Laboratory has multiple openings for a Scientific Engineering Associate in Berkeley, CA. Duties: Perform scientific data analysis using the scientific python stack
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local case studies Good programming skills, specifically R and Python Familiarity with statistical approaches used for model evaluation, including geostatistics and timeseries analyses Previous research
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Qualifications PhD in Aerospace Engineering, Mechanical Engineering, or a closely related field. Postdoctoral experience. Mastery of programming languages C++, Python + MATLAB. Preferred Qualifications Experience
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of fulltime research experience in data analysis and machine learning to include at least three years of research experience following the attainment of a Doctoral Degree. * Proficiency in Python, R, or similar
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related to experimental finance and asset markets. Programming experiments with z-tree, Python, and o-Tree. Experience in running computerized laboratory economic experiments. Recruiting, training, and
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electrophysiology and behavioral datasets. Use tools such as MATLAB, Python, or similar platforms for signal processing and statistical analysis. Maintain accurate records of data and experiments, adhering
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: Python (Django), Java (Spring), TypeScript (React), Docker, Terraform, GCP. We maintain a DevOps culture and use Scrum for our day to day work. We have also adopted an "open by default" approach to new
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. ● Proficiency in Python, R, or similar programming languages. ● Demonstrated ability to integrate and analyze diverse data types, including but not limited to: ○ Neuroimaging (e.g., fMRI, PET, DTI