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strong skills in the use of the analysis tools BORIS, R, and Python. Experience with international, particularly French, collaborations is considered an asset. You are fluent in spoken and written French
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: Will accept 48 months related experience in lieu of the Bachelor's degree for a total of 72 months experience Skills: Extensive computer programming/analysis experience in python, Matlab, R, or other
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., PowerShell, Bash, Python) to automate OS deployment, software distribution, and security patching. Serve as the lead technical expert and top-tier support for macOS and Windows OS system administration and
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computational tools such as Python or MATLAB Excellent team player that can also work independently High degree of reliability, organizational and interpersonal skills Service oriented approach towards researches
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at the interface of computational systems biology and mathematics/statistics with a strong attitude to open research software development. For more information visit http://www.fz-juelich.de/ibg/ibg-1/modsim
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for automated experimental systems used in high-throughput research. https://www.wpi-aimr.tohoku.ac.jp/en/about/staff/20260205_002130.html [Work content and job description] ●Develop and maintain control systems
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Inria, the French national research institute for the digital sciences | Rennes, Bretagne | France | 2 months ago
support services. The hired engineer will be a member of the KerData Inria team (https://team.inria.fr/kerdata/ ) led by Gabriel Antoniu. KerData is a joint research team of Inria Rennes - Bretagne
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reviews to guide experiment design and identifying emerging methodologies. Processing and analyzing large experimental datasets using scientific computing tools (Python/Matlab). Maintaining laboratory
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Expertise in FEM software (ABAQUS, ANSYS, SAP2000) and coding (Python/MATLAB). Professional engineering licensure (HKIE/CEng) or eligibility is a plus. Candidates for Professor or above should have
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skills with proficiency in Python, TensorFlow/PyTorch, and experience with containerized deployments and MLOps practices. Data Pipeline Engineering: Extensive experience with end-to-end data pipelines