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Field
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, environmental engineering, or a closely related field; Advanced knowledge of scanning Doppler wind LiDARs; Advanced knowledge in common statistical and spectral analyses; Knowledge of Matlab and Python; Preferred
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management (Matlab, MySQL) •May be trained to process neuroimaging data on the UMN MSI and CMRR servers: HCP and inhouse pipelines (e.g., ANACONDA, Python, FSL, AFNI, SPM, CONN) Managerial tasks, oversight and
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characterization (SEM, EDX, etc) Aerosol physics Data analysis and programming (e.g., MATLAB, Python, or R) Interdisciplinary teamwork Fieldwork and particle sampling e.g. on/from vehicles Swedish language skills
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Developing codes and ML models Maintaining Database Collecting pilot data for potential new projects Required Qualifications Experience in Machine Learning with expertise in Python and MATLAB Passionate in
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Experience in collaboration with industry or public sector organizations Knowledge of R, Matlab, Julia. High demands are placed on being able to plan, organize, document and follow up one's work independently
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to learn German Computer skills: MATLAB and/or R desirable You are motivated and self-propelled You are flexible and creative You should be a team player with high social skills What we offer: Work-life
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, and lab organisation Programming of experimental tasks and basic data analysis in R, Python, Matlab or similar Contributing to manuscripts for publication Assisting other colleagues in their research
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programming • Interest in geoscience and exploitation of data • Knowledge of hosting services like GitLab • Knowledge in Python, FORTRAN, MATLAB, HTML, or similar. Experience with Typo-3 is appreciated
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professionals aiming to lead in the AI-driven digital economy. Here are the key qualifications and requirements for admission : Master of Computer Science Degree Good programming skills (Julia, Python, Matlab
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, programs, and policies. The following skills are desirable: Experience with data analysis and data analysis and visualization software (R, Matlab, Stata, or other). Familiarity with using mental models