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Field
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machine learning for the next generation of AI models – uncertainty-aware foundation models, generative models and world models – with the support of competent and friendly colleagues in an international
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is BTH's largest department, with just over 70 employees. The department conducts research in computer science, covering the subfields of big data and AI, parallel computer systems, visual and
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Engineering, we are seeking a researcher with a strong interest in developing and applying machine‑learning methods for materials design, in particular steel design. The position is part of our growing research
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, Machine Learning, Robotics and Robotic Learning, Human-Robot Interaction, and Natural Language Processing. Together with the Dept. of Automatic Control, the division operates RobotLab LTH, which gives
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sciences. Its vast scope also benefits our undergraduate and graduate programmes, and we now teach courses in several engineering programmes at bachelor’s and master’s levels, as well as the programmes in
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development practices (e.g., XR, VR, computer graphics, and programming); and play in participatory, learning, and societal contexts (e.g., STEAM education and live-action role-playing). Link Application
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through a model-driven approach, i.e. a combination of simulation- and data-driven methods and tools with data analysis and machine learning as an important part. The work builds on established theories and
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new methods for integrated sensing and communications in optical networks. Cutting-edge machine learning techniques for sensing data analysis, models of the impact of external phenomena on optical
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. In addition, the following are requirements for the role: Strong programming and quantitative skills, particularly in Python and/or R. Experience in deep learning, machine learning, or large-scale
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development practices (e.g., XR, VR, computer graphics, and programming); and play in participatory, learning, and societal contexts (e.g., STEAM education and live-action role-playing). Link Application