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regional climate modelling, good knowledge of programming in Matlab/Python, Fortran/C, Bash, and working in an HPC environment, published scientific papers, and be fluent in written and spoken English. Where
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projects that rely on computational modeling and machine learning approaches. The postdoc will help bring these projects to completion, carry out the required validations, and take the lead in preparing
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modelling is a valuable tool to revealing the source of UTLS aerosols, the origin of water masses, and formation processes of cirrus particles. Your key responsibilities include: Preparation, operation, and
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this collaborative project, we will develop a comprehensive strategy combining (1) vasculature-on-chip models, (2) in-depth nanobubble characterization, and (3) tailored imaging solutions to advance cancer diagnostics
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to perform CUT&RUN analysis of genes regulated by NRF2 isoforms in selected cell models. That also requires the preparation of DNA library for the NGS sequencing. Another aspect to study during this time is to
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especially crucial in applications such as medical diagnosis, weather forecasting, and aircraft design. To improve the reliability and trustworthiness of mathematical models and machine learning tools (e.g
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Digital Business team in this teaching-focused role, where you’ll help shape the next generation of digitally fluent business graduates. You’ll coordinate and deliver undergraduate and postgraduate courses
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USNH Employees should apply within Workday through the Jobs Hub app A postdoctoral research associate is required in the Engineering for Agri-Environment Lab (https://sites.usnh.edu/eaelab/), led
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participation in such a project. - Be fluent in French and English. Website for additional job details https://emploi.cnrs.fr/Offres/CDD/UMR5213-DELDAL-033/Default.aspx Work Location(s) Number of offers
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composition, production and performance. Improve existing datasets and create new ones useful for deep learning models Where to apply Website https://apply.interfolio.com/178410 Requirements Research