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increasing independence over time. Collaborate on project and analysis design guided by their PI. Develop new computational methods. Adhere to field and lab standards for data analysis. Identify, process
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. A 129, pp. 6470-6481; J. Chem. Theor. Comp. 21, pp. 6305–6314 (2025). Duties and Responsibilities Carry out research in theory and code development and the processing of large-scale simulations using
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4 Dec 2025 Job Information Organisation/Company CNRS Department Institut matériaux microélectronique nanosciences de Provence Research Field Chemistry Physics Technology Researcher Profile
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3 Dec 2025 Job Information Organisation/Company MOHAMMED VI POLYTECHNIC UNIVERSITY Research Field Physics Chemistry Researcher Profile Recognised Researcher (R2) Established Researcher (R3) Country
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have a strong interest in both theory and numerical work. Numerical work involves code development (e.g., changing the C++ LAMMPS code, programming of data analysis tools, etc.), carrying out large-scale
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information about the Bezdek Group can be found on our Website . Questions regarding the position should be directed to Prof. Dr. Máté J. Bezdek email (mbezdek@ethz.ch ). Please note that we exclusively accept
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Inria, the French national research institute for the digital sciences | Palaiseau, le de France | France | 5 days ago
4 Dec 2025 Job Information Organisation/Company Inria, the French national research institute for the digital sciences Research Field Computer science Researcher Profile Recognised Researcher (R2
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. Coordinating studies involving human participants; Processing and analyzing biological samples; Data management including handling large data sets and performing statistical analysis; Communicating results
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interstellar medium”, funded by the Swedish Research Council (PI: J. Kainulainen). In this project, we combine novel observational data, such as Gaia-based dust density measurements, with advanced modeling
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 12 hours ago
and its core data science libraries (e.g., TensorFlow, PyTorch, Scikit-learn, Pandas, NumPy). Data Engineering: Experience in building and managing large, multi-modal data pipelines and repositories