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, mixed-effects modeling, Bayesian methods, deep learning, variational autoencoders, generative AI). Is an experienced programmer in R and/or Python, and used to working with large datasets and reproducible
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of biomass conversion technologies. Experience in programming with Python. Experience in Life Cycle Assessment. Experience in techno-economic analysis. Experience in scientific writing and communication
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or more of the following areas: IoT, data mining, cloud/edge/fog computing. • Good knowledge in one of the following programming languages: C/C++, Python. Place of employment: Karlskrona. Employment level
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and ability to communicate clearly Merits include: Knowledge of LLMs, deep learning, and Python programming Knowledge of power electronics Experience in modelling, simulation, and experimental work In