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: Experience in deep learning, machine learning and medical imaging processing Programming experience: Python, MATLAB, SPSS, Shell. Experience in working with Linux workstation. Excellent verbal and written
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required for this position. Skills: Not Applicable Driver's License: A driver's license is not required for this position. More About This Job Preferred Qualifications: Seeking experience in MATLAB
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in Python (R and Matlab); • Familiarity with large-scale data processing and cloud computing (Google Earth Engine, BDC, AWS). Application: Send a cover letter (1 page), updated CV, and two references
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research interests, and three letters of reference, should be submitted through the application portal located at: https://indiana.peopleadmin.com/postings/31658 Review of applications will begin on January
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or seabed mining. The candidate will join the Functioning and Vulnerability of Marine Ecosystems group at ICM-CSIC: https://www.icm.csic.es/en/research-group/functioning-and-vulnerability-marine-ecosystems
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National University of Science and Technology POLITEHNICA Bucharest, Pitesti Branch | Romania | 16 days ago
mathematical models, advanced simulations in MATLAB/Simulink, validating the models through experimental data and interpreting the results in the context of electrolyzer performance and degradation
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Balears (UIB) / University of the Balearic Islands (UIB) Where to apply Website https://ppi.uib.eu/ Requirements Research FieldEngineering » Computer engineeringEducation LevelBachelor Degree or equivalent
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appropriate tools (R, Matlab, FSL, SPM) and advanced statistical techniques (e.g. linear mixed-effects models). The PDRA will have responsibility for writing up the study results for publication in high-quality
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and improve custom-written LabVIEW and MATLAB scripts for data acquisition and analysis. General molecular biology and recombinant protein preparation. Maintain clear and comprehensive laboratory
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. Proficiency in Python, MATLAB, or R. Strong quantitative and analytic skills. Preferred Qualifications Experience with evidence-accumulation models (DDM, sequential sampling, Bayesian models). Experience with