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analysis to estimate ecological parameters, and implementing models in Matlab. You will work closely with a diverse team of around 20 field ecologists and modellers, as well as international collaborators
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MATLAB, Python, or similar platforms, with strong statistical analysis skills. The University of California is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive
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Laboratoire de Physique des Interfaces et des Couches Minces (LPICM), UMR CNRS/École Polytechnique, | Palaiseau, le de France | France | 4 days ago
measurement systems, with in-depth experience in languages like MATLAB, Python, C/C++, and LabVIEW. Basic understanding of electronics and embedded systems. Methodical, rigorous, creative, and challenge
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and TMS-EEG data acquisition and analysis, as well as familiarity with high-field MRI workflows. Proficiency with use of established EEG analysis toolkits (e.g. Matlab, FieldTrip and EEGLAB). A
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knowledge in at least of the following techniques : EEG, MRI, TMS • Good programming skills (python, R, matlab). • Knowledge of legal and deontological frameworks • English : B1 to B2 Know-how • Organise
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, MATLAB). excellent written and verbal communication skills. proven ability to work collaboratively in a team setting. Pre-employment checks Your employment is conditional upon the completion of all role
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. These experiments will be combined with optogenetic tools for causal manipulations of neural circuits during learning and sleep. Additionally, data analysis using MATLAB (or Python) will be used to analyse neural
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computational skills, with experience in advanced data analysis and statistical methods Proficiency in computer programming, ideally in MATLAB, Python or similar tools for scientific data analysis and
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numerical work (35%) Minimum Qualifications: PhD in Ocean Engineering or related field Experience with programming and analysis in Matlab or similar programming language Experience with hands-on experimental
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models, statistical analysis). Proficiency in programming languages (e.g., R, Python, MATLAB) and familiarity with relevant air quality modeling tools. Experience with large datasets and data processing