53 development-"https:"-"https:"-"https:" Postdoctoral positions at Aarhus University
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the department have established companies to develop new medicinal treatments founded in professional scientific basic research. You can read more about the department here and about the faculty here . About the
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play a central role in developing, evaluating, and interpreting deep learning models for multi-sensor satellite data, addressing challenges such as spatiotemporal learning, super-resolution, and model
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neuromuscular research and molecular muscle biology your position is primarily research-based but may also involve teaching assignments. You will contribute to the development of the department through research
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supervision experience at the BSc and MSc level Interest and experience in developing competitive national and international research applications Experience in planning and conducting molecular laboratory work
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/or large genetic datasets. This may include genetic analyses, causal inference, epidemiological analyses, and clinical prediction modelling using machine learning approaches, and development
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fixed term contract for 36 months. Research staff at King’s are entitled to at least 10 days per year (pro-rata) for professional development. This entitlement, from the Concordat to Support the Career
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will be part of a research environment focusing on integrating multi-source satellite remote sensing data and developing novel algorithms to quantify agroecosystem variables for environmental
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-year extension. The project is fully funded by the Independent Research Fund Denmark (DFF). The main objective of this project is to develop physics-constrained, data-driven turbulence models
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. Specifically, the postdoc will develop and test up-scaled microbial electrosynthesis reactors involving advanced electrochemistry, reactor design, and scaling approaches. Expected start date and duration of
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Research Focus We are offering a Postdoctoral position in graph machine learning, algorithms, and graph management with particular focus on: Modeling real-world spatio-temporal energy networks Developing