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analytical and mathematical skills, including proficiency in quantitative modeling, data analysis, and scientific computing (e.g., R, Python). Strong written and verbal communication skills in English. *for
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programming languages like Python or Matlab environment. Knowledge for programming (python) would be a plus for the force curves interpretation since some codes have been developed for the 3D -AFM data analysis
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circumstances. Is comfortable using digital learning tools and platforms such as Python, VS Code and Tableau. Holds, or will soon complete a doctorate in Engineering, Physics, Computer Science, Mathematics or a
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using digital learning tools such as R, Python, Stata or Matlab, and has strong data skills. Holds, or will soon complete, a doctorate in a relevant discipline. Desirable qualities include experience
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to changing needs. Is confident using digital learning tools and programming languages such as R, Python and C++. Holds, or will soon complete, a doctorate in a relevant discipline aligned with Data Science
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DC-26094– POSTDOC/DATA SCIENTIST – AI-DRIVEN CLIMATE RISK MODELLING AND EARLY WARNING SYSTEMS FOR...
: https://www.list.lu/ How will you contribute? You will be part of LIST’s Remote sensing and natural resources modelling group Embedded in the Environmental Sensing and Modelling (ENVISION) unit
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 3 months ago
Website https://jobs.inria.fr/public/classic/en/offres/2026-09697 Requirements Skills/Qualifications Technical skills and level required: Good skills in Python programming and/or C++ Good skills in Linux
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, Computational Biophysics, or a closely related field Strong programming skills (e.g., Python, C/C++) Knowledge of machine learning frameworks (e.g., PyTorch, TensorFlow) Very good English language skills, ability
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.PEX and DOI identifier https://doi.org/10.54499/2024.15642.PEX ), financed by Fundação para a Ciência e a Tecnologia, I.P. through national funds under the 2024 Call for Exploratory Projects in All
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software (e.g., R, Python, PLINK, SAIGE). Familiarity with chronic kidney disease phenotypes and population-based studies. Excellent organizational, communication, and documentation skills. Ability to work