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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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contribute to the development of teaching and learning within the subject area. The research can be based on controlled experiments as well as production data from commercial farms, questionnaire-based studies
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addition to conventional software, the scope includes engineering of AI enabled systems (primarily ML and LLM), and thus MLOps (Machine Learning Operations), datacentric AI, and legal and ethical aspects of AI
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. The successful candidate will also contribute to the development of teaching and learning within the subject area. The research can be based on controlled experiments as well as production data from commercial
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, or a related field. It is an advantage if you have experience with probability theory, reinforcement learning, or Markov Decision Processes. Coursework or project experience in multi-agent systems
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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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, multi-omics data integration using machine learning, and potential collaborations with clinical and translational researchers. The project is well-suited for candidates with a background in bioinformatics
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Learning has an open position for a doctoral student with a background and strong interest in deep generative learning and computer vision/remote sensing. The successful candidate will join a project funded
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, or a related field. It is an advantage if you have experience with probability theory, reinforcement learning, or Markov Decision Processes. Coursework or project experience in multi-agent systems
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university transcripts. Other qualifications(advantages) For the doctoral programme in question, the following are considered as other qualifications: Strong foundations in Machine learning and reinformement