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research assistant professor (post-doc) in the project "Structural properties of nonlinear control systems: static and dynamic linearization, symmetries, observers" financed under the OPUS 27 program of
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research related to the dynamics of viral replication and the immune response in humans during natural infection with respiratory viruses. You will analyze longitudinal viral and immune samples collected
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involves working with a range of stakeholders to develop communication strategies, conduct qualitative and mixed methods research, generate data, analyse findings, and deliver public engagement. The post
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environment. SEMS is one of the UK’s leading research-intensive universities, recognised for delivering world-class education and impactful research. The School offers a dynamic and interdisciplinary research
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Aarhus University is seeking three postdoctoral fellows for research on metabolic dynamics and pl...
of the team of Prof. Alfred Spormann in the Department of Chemistry at Aarhus University to engage in cutting edge systems-level research in metabolic dynamics and plasticity of acetogens during gas
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 3 days ago
Hiring Range Proposed Start Date 06/01/2026 Estimated Duration of Appointment 12 Months Position Information Be a Tar Heel! A global higher education leader in innovative teaching, research and public
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state-of-the-art statistical and mathematical methodology to improve understanding of epidemic dynamics and control. They will work on one of the new projects starting in the Unit, including i) analysing
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, Clinical, and Health Psychology, including their intersections Language requirements: Fluency in English and German or French is required We offer A modern, dynamic university with a personal and inclusive
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public health with research strengths across a range of health disciplines, including infectious diseases and immunisation. SPH has a core focus to investigate and provide new knowledge to help inform
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Zanna, the successful candidate will focus on developing generative machine learning models for complex dynamical systems for probabilistic forecasts. The postdoc will be expected to lead independent