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applications. Experience in natural language processing, model evaluation, or experimental design is advantageous. Proficiency in Python and/or R and familiarity with AI/ML libraries or generative AI platforms
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for data acquisition and analysis (e.g., Python or LabVIEW) are highly desirable. After a training period, you will operate and maintain the fast EC-STM system and contribute your own ideas to the project
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candidates will have: A solid grounding in mathematical or physical sciences Interest in dynamical systems and complex system behaviour Some coding experience (Python and/or Julia) Enthusiasm for working
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should have documented background in the following areas: Electrodynamics Data analysis for scientific applications Programming (e.g., Matlab, Python, C, C++) for scientific applications Previous
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image processing/?tomography - advanced programming skills in Python - excellent command of English (written and spoken) Assets: - team-oriented mindset with strong communication and organizational skills
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/deep learning and image processing/tomography advanced programming skills in Python excellent command of English (written and spoken) Assets: team-oriented mindset with strong communication and
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experience with molecular simulation and scripting and/or programming languages (e.g. python) is a plus. The start date of the studentships is 1. October 2026. Due to restrictions by the funder
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the University of Lleida. Responsibilities and tasks The overall aim is to develop methods and models (mainly in Python and OpenModelica) for optimization, and analysis of scale-grid systems integrated with power
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language (e.g., C++, Python), creative approach to solving work tasks, strong motivation for research and the ability to work both independently and within an international collaboration. Contract and
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and microstructure-based modeling Experience with numerical methods for PDEs Programming skills in Python (knowledge of C++, Fortran or HPC is a plus) Scientific curiosity and critical thinking Ability