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tasks Development and implementation of behavioral protocols Analysis of imaging data Programming analysis tools (Python/Matlab) Associated activities: Participation in team meetings and seminars
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skills experience with Matlab, Stata, R or Python; A high level of intellectual curiosity, analytical rigor, and a strong commitment to policy-relevant research. LanguagesENGLISHLevelExcellent Additional
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stereotaxic procedures Prior experience in analyzing experimental data in MATLAB and/or Python. See Table 24B for the salary range for this position. A reasonable estimate for this position is $75,600-$194,800
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publication track record in international scientific journals Demonstrated experience in ecological or oceanographic data analysis Proficiency in R, Python, Shell script, or MATLAB Experience working with CMIP
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. Certifications/Licenses Required Knowledge, Skills, and Abilities Laboratory or experimental research experience Experience with common programming languages (e.g., Python, Matlab) Experience working with big data
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, Neuroscience, or a related field by the start date. Demonstrated expertise in computational modeling of human behavior or computer vision / machine learning. Proficiency in Python, MATLAB, or R. Strong
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to the following: - Skills in Python, ROS and Matlab - Skills in robotics and machine learning - Being enrolled on or having passed any master’s degree in engineering. Language requeriments B2 English. Years
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the Regulatory Certificaytion for animal experimentation - Python and/or Matlab programming for data analysis, a proven track record of previous achievements in this domain is needed - Ability to work in a team
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of Brice Bathellier (Institut Audition), Virginie van Wassenhove (NeuroSpin), and Mehrdad Jazayeri (MIT). Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/SNC9138-SRDOST-008/Candidater.aspx
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Inria, the French national research institute for the digital sciences | Paris 15, le de France | France | 28 days ago
hyperscanning neuroimaging data, using advanced statistics and machine learning methodologies for temporally-sensitive data, such as GLMM, Random Forests, LSTM, etc.. Use of MatLab for pre-processing, and