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triggered by colloids, as well as methods for immobilizing these ions. Modern methods of theoretical chemistry (first principles, kinetic Monte Carlo, machine learning) will be applied to investigate
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Python for scientific computing – experience with data analysis and basic signal processing – foundations in machine learning and interest in developing advanced AI models – familiarity with Linux
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well as the programmes in statistics, cognitive science and innovative programming. Read more at https://liu.se/ida The position is based at the Division of Statistics and Machine Learning (STIMA). We conduct research
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application (max. 5 pages) Application: We are looking forward to receiving your online application. The full, legally binding call for application (in German) including the salary can be found here: https
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of the Grant are:; 1) To apply machine learning algorithms for the diagnosis of faults and malfunctions in photovoltaic plants, using data from SCADA systems combined with synthetic data from digital twins (DT
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Experience and practical knowledge of programming languages and tools (e.g. Python, Java, etc.) Knowledge in Software Engineering, AI, machine learning is an advantage Experience with software observability
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scientific coding skills in Python. You are strongly motivated to acquire advanced skills in Python and Fortran and in the use of high-performance computer systems you have affinity and preferably experience
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to optimise built-environment thermodynamics and occupant comfort by creating predictive AI tools for spatiotemporal heat transfer. Machine learning algorithms will identify energy inefficiencies and propose
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, network analysis, or machine learning are a plus Good organisational skills and ability to work both independently and collaboratively Effective communication skills and an interest in contributing to a
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artificial intelligence, computer science, engineering, mathematics, physics, or a related discipline Demonstratable background in machine learning, information retrieval or natural language processing