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whole-genome duplication across diverse plant systems (see https://www.yantlab.net/ ). The project is funded through a Formas grant aimed at restoring European ash (Fraxinus excelsior) populations
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collaborations Experience with evidence synthesis, meta-analysis, or other comparative methods Experience in experimental research with animals or other biological systems Experience in field ecology, animal
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projects within the lab’s research program Perform in vivo calcium imaging and behavioral experiments Analyze neuronal and microglial activity datasets (e.g., calcium imaging) Conduct immunohistochemistry
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You are expected to be somewhat accustomed to teaching, and to demonstrate good potential within research and education. The following experience will strengthen your application: It is highly
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. Experience in any of the following counts as a strong merit: causal inference with observational data, text as data, large language models, mechanistic interpretability, or semiparametric and design-based
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regions by developing interpretable and efficient methods in comparative pangenomics, leveraging machine learning methods, statistical analysis and efficient algorithm and data structures (https
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research and the application of XRD-CT. Develop experimental research exploiting XRD-CT for battery research. Participate in the BatMAX consortium, including planning beamtimes, conducting experiments
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experience in statistical modelling and/or machine learning for regression or distribution estimation, and in time-series or signal processing; proficiency in Python. Advantage: Hands-on field or experimental
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for experimental control, phase retrieval, and reconstruction. It will also include development of best practices for nanoCT on batteries, focusing in particular on minimizing radiation damage and enabling in
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writing and reviewing scientific publications. Excellent communication and interpersonal skills. Practical mining-related experience is a plus. Interest in and ability to work in a multidisciplinary and