81 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "The Institute for Data" positions at University of Lund in Sweden
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you are expected to acquire basic knowledge of Swedish during the employment period. More information about the doctoral programme is available at: https://www.soclaw.lu.se/en/research/doctoral-studies
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conferences, as well as opportunities to participate in pioneering interdisciplinary projects. More information about the doctoral programme is available on the department’s website: (https://www.iko.lu.se/en
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background and interest in soil microbial ecology, ecosystem ecology and biogeochemistry. You will be part of the Microbial Biogeochemistry in Lund (MBLU) research environment (https://portal.research.lu.se/en
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at the intersection of numerical analysis, uncertainty quantification, and scientific machine learning. The research will primarily focus on probabilistic methods for data-driven model reduction, with
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and computer vision. Understanding or willingness to learn advanced statistical modeling is a plus Assessment criteria and other qualifications: This is a career development position primarily focused
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particular, the candidate will work on the development of novel deep-learning reconstruction algorithms to retrieve 3D and 4D (3D+time) imaging acquired by advanced X-ray imaging techniques. Such developments
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about working with us Work at Lund University | Lund University Ready to shape the future of research? Find more reasons why Lund University and the HT Faculties is right for you here , and learn more
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Work at Lund University | Lund University Ready to shape the future of research? Find more reasons why Lund University and the HT Faculties is right for you here, and learn more about Working in Lund
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Information Technology conducts broad research in cryptography, computer security, wireless and wired networks. The Security Group has around 20 members. The main research areas are cryptography, privacy, and
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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. The empirical