96 engineering-computation "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" positions at University of Lund
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an emphasis on maintaining physical consistency, numerical stability, and real-time data assimilation within reduced-order models. Primary application areas include computational physics and climate modeling
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information about doctoral studies is available on the department’s website: https://www.iko.lu.se/en/research/doctoral-studies The recently established research environment “Radiation Safety and Society
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on lth.se. https://www.lth.se/english/study-at-lth/phd-studies/ Subject and project description The doctoral student will work on the project ‘Heating, transport, and participation in life: Towards
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doctoral degree. More about being a doctoral student at LTH on lth.se . Subject and project description The study subject is computer science with focus on software technology supporting development
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models and computational statistics. We are looking for a promising early-career researcher who can advance research in statistics with a focus on data science and teach the next generation of students. As
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. in natural sciences or engineering, with a strong scientific background and specialization in biophysical characterization methods. Demonstrated hands-on experience working with large-scale research
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University School of Economics and Management (LUSEM)": https://lusem.prodwebb8.lu.se/sites/lusem.lu.se/files/2024-02/general-requirements-profile-and-assessment-for-employment-as-senior-lecturer-at-lusem.pdf
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relevant field for the subject area, or a second-cycle degree in civil engineering, environmental engineering, or similar Additional requirements To benefit from the current doctoral program, the following
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through pioneering projects and research ideas? If so, you now have the opportunity to start as an assistant professor (associate senior lecturer) as part of Lund University Programme for Global Excellence
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Information Science (GIS), and computational science for health and environment, to study processes spanning from the microscopic to the planetary, across all time scales. The Inverse Modelling group at the Department