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for these frameworks, and use them to analyze key performance indicators such as achievable rates, coverage, and energy efficiency, as well as optimize relevant system parameters. Applicants must hold a PhD degree or
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from the areas of few-shot learning, continual learning and modular deep learning, as well as different LLM alignment frameworks, based on reinforcement learning and direct preference optimisation
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Deep Learning libraries (e.g., Pytorch, Tensorflow, Keras) will be considered a significant advantage; Previous experience in image processing and\or computer vision will be considered an advantage
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such as achievable rates, coverage, and energy efficiency, as well as optimize relevant system parameters. Applicants must hold a PhD degree or terminal degree from a recognized institution of higher
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models and transformer-based architectures to construct high-dimensional design spaces. These models are integrated with Deep Reinforcement Learning (DRL) for fine-tuning or end-to-end learning, enabling
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available from July 2026. The research group studies functional immunogenetics and adaptive immunity - particularly in relation to autoimmune diseases (https://www.med.uio.no/klinmed/english/people/aca
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candidate would be a PhD in geophysical sciences, computer science, or machine learning with experience in developing and verifying deep learning-based models for large dynamical systems (e.g. weather
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% for PhDs and TV-L E14, 100% for PostDocs; 45k - 57k Euro / year + benefits). For interns, we offer a stipend to cover living expenses. Click here to learn more about our research. Topic / Area: The
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of AI and Data Science : Machine and deep learning, NLP, BDI (Belief-desire-intention) systems, and Large Language Models (LLMs). Expertise in design and very good programming skills (Python, Pytorch
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will also have good opportunities to learn from and socialize with other postdoctoral fellows at the department. For more information about the department: https://www.slu.se/en/about-slu/organisation