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and future developmental timepoints from time-series data. Our recent theoretical work suggests that these learned relationships can generalize across conditions, and we will test this using both
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possess strong programming skills in Python. Experience in human behavior research, computational behavior modeling, and AI/machine learning methods for time-series analysis is advantageous. Particularly
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Description of the Workplace Cancer arises through a series of changes in the genetic material of previously completely normal tissue. Through these genetic changes, cancer cells can evade the
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equality and diversity as a strength and an asset. Description of the Workplace Cancer arises through a series of changes in the genetic material of previously completely normal tissue. Through these genetic
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and forestry. Climate change poses a new threat to hair lichens, but its effects are so far poorly understood. This project uses a long time series (ca. 50 years) of eDNA samples collected in
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comprehensive range of techniques including, but not limited to, mice infection via gavage and intraperitoneal injections, necropsy, paraffin tissue embedding, tissue sectioning, multiplex immunofluorescence
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Expert Survey on party positioning (CHES), you will work with the project PI to develop and run a series highly-focused expert surveys with the purpose of unpacking and understanding the positions
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cultivars with strong resistance against virus yellows. The project is carried out in collaboration with Nordic Beet Research and KWS Scandinavia, and it has financial support from SLU Grogrund, Centre
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to join our team. With Björn Lindström as teamleader and funded by the Bank of Sweden Tercentenary Foundation, we are studying how human-AI collaboration can improve human collective innovation. Our
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highly qualified postdoctoral researchers to join our team. With Björn Lindström as teamleader and funded by the Bank of Sweden Tercentenary Foundation, we are studying how human-AI collaboration can