22 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"Linköpings-University" positions at University of Lund in Sweden
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protection and security, work environment safety and environmental safety at the MAX IV Laboratory. The team is now looking to employ an expert within machine safety. As the sole machine safety engineer, you
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for near-real-time monitoring of crop growth and early yield prediction, combining remote sensing, machine learning, and crop modeling to support sustainable agriculture. Within the project, we will estimate
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biomarker detection. This requires the use of machine learning techniques including the production of training data by simulation of optical fields. The project also includes guidance of experiments aiming
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or Seaborn and more. Parallel programming (MPI, OpenMP, CUDA) Knowledge in the scientific build environment EasyBuild. General knowledge of Artificial Intelligence and Machine Learning. AI/ML. Knowledge
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qualifications Ongoing full-time enrolment in a master’s programme by the faculty of science Advanced programming skills in Python and R Advanced proficiency in ArcGIS and/or QGIS Experience with machine learning
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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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of the following areas: state models, time series analysis, computational statistics, unsupervised machine learning, optimisation, model predictive control. Experience in financial mathematics. Having high integrity
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dimensionality reduction methods), systems biology analysis (including machine learning and other AI techniques), statistical tools focusing on analysis of complex longitudinal data, and how different types
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test multi applications. Within this project we will design a ultrabroadband and a high spectral resolution hyperspectral lidar. The development is done by raytracing, Computer Aided Design and 3D
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hyperspectral lidar technology and test multi applications. Within this project we will design a deep ultraviolet and a aquatic hyperspectral lidar. The development is done by raytracing, Computer Aided Design