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Field
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This position focuses on investigating vehicle-track-ground interaction dynamics with a particular emphasis on the critical speed induced by high-speed trains. The candidate will contribute
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presentation of analysis results. The ability to work with large and complex datasets. Excellent spoken and written English skills. Experience in machine learning, predictive modeling, and/or Bayesian methods
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current and next-generation galaxy and time-domain surveys. You will work closely with our teams on the Rubin Observatory ‘s LSST, Euclid, ZTF, and LS4. Main responsibilities Field-level inference and
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fungal communities may be changing through time, and infer the functional significance of this, in terms of changes in organic matter composition, and C accumulation rates. About the position The postdoc
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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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Network Inference https://www.umu.se/en/ucmr/ec-postdoc-programme/ncrna_net-development-of-a-novel-approach-to-lncrna-mrna-regulatory-network-inference/ 7. Virome–vector competence shifts: How mosquito
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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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well as a detailed plan to conduct fieldwork in Sweden, Finland or The Netherlands. Track record in sustainability, degrowth, postwork, social movements, or similar. Excellent English language skills
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Collaboration with PhD student responsible for experimental testing If there is interest, some experimental testing may be carried out Participating in project meetings and summarizing of results Keeping track
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. The Fellowships are tenure-track positions with the host organizations, which assume the responsibility for the long-term faculty appointments following a tenure evaluation. The future of life science is data