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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
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modeling Programming skills in Python and machine learning packages such as PyTorch and TensorFlow Scientific curiosity and critical thinking Ability to work in interdisciplinary environments Motivation
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of our experienced group members. • Participate in the development of theories, collaborate with the top experimentalists, and perform numerical simulations (matlab/python/mathematica). Key Requirements
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/Qualifications Candidates must have a master's degree, preferably with a background in semiconductor physics. Basic knowledge of electronics and Python programming would be appreciated. Applicants must have a keen
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well as programming skills (Python required; experience with seismic data processing is advantageous) Initial experience seismic data analysis and/or wave propagation modelling is an asset Willingness to participate in
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excellent analytical and programming skills (for example in Stata, R or Python), experience working with data, and an enthusiasm for interdisciplinary research that bridges data science, healthcare, and
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, computer science, or a closely related discipline (typically first-class or high 2:1, or equivalent; Master’s welcome) • Strong programming skills (for example Python, MATLAB, C/C++) • Strength in at least two of