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We are seeking a highly motivated and skilled Postdoctoral researcher with interdisciplinary expertise to develop risk assessment and mitigation models using Large Language Models (LLMs
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measurements to the results of existing techniques using backscatter to quantify forest attributes through synthetic aperture radar imaging. The overall project, spanning multiple institutions, aims to produce a
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relevant for the position, including experimental microbial microcosms and ecosystem-scale microbial community analysis A minimum of 3 years’ postdoctoral experience relevant for the subject of the position
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/deep learning to improve workflows related to antibody engineering. Have documented experience from development of therapies for oncology applications. Have or have had a postdoctoral appointment. Have
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fluorescence microscopy (from single-molecule imaging to intravital microscopy), electrophysiology, respirometry, microfluidics, organoid cultures, bioprinting, and excellent opportunities to work with various
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) classification and utilization based on advanced AI technologies, such as regenerative AI, image processing and reinforcement learning, that can improve the energy efficiency and reduce the operating cost and
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internationally recognised research develop, lead, and participate in teaching at first, second and third cycle level supervise PhD students and postdoctoral researchers collaborate with other research groups
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to assess and ensure the safe, predictable, and transparent behavior of systems incorporating machine learning and generative models. Design and prototype frameworks or tools that support systematic V&V
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-cycle courses and study programmes and responsibility for postdoctors. As a principal supervisor, the applicant should normally have supervised doctoral students throughout their studies and until
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wastewater treatment. The teaching staff consists of approximately 15 faculty members, supported by several postdoctoral researchers and approximately 25 doctoral students. The research is further supported by