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at SLU by visiting: https://www.slu.se/en/about-slu/work-at-slu/ Location: Uppsala Form of employment: Temporary employment 24 months, with the possibility of extension. Scope: 100% Start date: As agreed
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aspects of both. The first direction concerns the data-driven discovery of dynamical rules underlying developmental trajectories. The aim is to develop and analyze quantitative frameworks that learn
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of Medical Biosciences, which offers an international, collaborative, and open-minded research environment. Please visit the lab’s webpage for more information: https://erdemlab.github.io . The Erdem research
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network modelling and machine learning for regulatory inference. - Functional validation of candidate TE‑CREs in spruce using UPSC transformation and somatic embryogenesis pipelines; evaluating drought
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-microbe interactions, mycology, and microbial ecology. The position is placed in the Forest Microbiology group. Read more about what it is like to work at SLU at: https://www.slu.se/en/about-slu/work-at-slu
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complex behavior under demanding operating conditions presents a significant modeling challenge. This project addresses that challenge by combining machine learning with constitutive modeling, while
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projects in data-driven nutrition, such as: statistical modelling, AI, and machine learning on large epidemiological cohorts, diet and health data analysis of omics data (metabolomics, proteomics, microbiome
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. The department will provide support with language learning. Eligibility The applicant must meet the following qualification requirements: PhD or equivalent academic qualifications research expertise in
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the Department of Biology. More information about the group’s research can be found here: https://www.biology.lu.se/caroline-isaksson. Qualifications Applicants must be able to demonstrate evidence of: Some
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. Lead and conduct research projects in data-driven nutrition, such as: statistical modelling, AI, and machine learning on large epidemiological cohorts, diet and health data analysis of omics data