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machine-learning tools. Data analyzed include precursors such as volatile organic compounds, aerosol number and mass concentrations, chemistry, biological particles, cloud and ice condensation nuclei, light
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for machine learning, e.g. PyTorch or TensorFlow. Strong ability in spoken and written Swedish. Assessment of the applicants will primarily be based on scientific merits and potential as researchers. Special
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factor that strongly modifies turbulence, pressure drop, and heat transfer. Unlike conventional machined roughness, AM roughness is characterized by randomness, porosity, and powder adhesion, producing
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