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Close collaborations with the New York Genome Center and with the infrastructure platforms at SciLifeLab An opportunity to develop an internationally competitive research profile and networks as
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analysis, work with large language models, network analysis, causal inference in machine learning and agent-based modelling. Experience in collecting, curating and analyzing large digital datasets with
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activities aiming at developing soft skills and at strengthening networks and collaborations in academia and industry. Be part of a strong postdoc community. The Umeå Postdoc Society fosters networking and
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networks are controlled, to develop predictive models of methane cycling in northern rivers. This postdoc position will focus on assessing how stream methane emissions are linked to permafrost thaw, using
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, and engage with a vibrant network of national and international collaborators. The recruited candidate will work in the AIMLeNS lab lead by Assoc. Prof. Dr. Simon Olsson at Chalmers University
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relevant duties/assignments within the subject area. Other merits The scientific work is conducted within the research group as well as in association with a larger collaborative scientific network, and good
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analysis, work with large language models, network analysis, causal inference in machine learning and agent-based modelling. Experience in collecting, curating and analyzing large digital datasets with
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written and spoken. Strong communication and organizational skills, as well as a demonstrated ability to produce high-quality results within set deadlines, are essential. Personal motivation and suitability
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communication by participating in national and international meetings, and support service for analytical equipment. Publishing popular science and scientific articles is a central part of the work
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to tax. The PI covers running costs for the project. Project description What if we could decode the hidden language within plant genomes that controls their resilience to climate change, their growth