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`liquid-liquid phase separation' (LLPS). We will use programmable, multi-component model systems of biomolecular phase separation to investigate the transport of biomolecular information, stress, and light
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photoreceptive pathways using mouse as a model system. Methods used in the lab include various in vitro, ex vivo and in vivo approaches, as well as functional and behavioral studies of relevant opsin knockout mice
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on climate impact research and process-based modelling of biogeochemistry, agronomy, biology and geography from Aarhus University and University of Copenhagen, as well as international partners. Field
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October or as soon as possible thereafter. Jobdescription This postdoc position offers a unique opportunity to bridge environmental modelling, behavioral insight, and policy innovation to understand and
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magnetic experiments in the GFZ laboratory for Earth Magnetism in Time and Space, assessing the reliability of the magnetic signals and age-depth models for the cores and interpreting the determined field
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Postdoc in assessing carbon sequestration potential of different wetlands as nature-based solutio...
five bioclimatic zones. Your task will be to combine multi-source data — including field observations, environmental measurements, and satellite imagery — with mechanistic models to assess carbon
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systems, or network analysis. Experience with methods for causal inference, or modelling of biological systems is also considered a merit, along with prior work involving large-scale sequencing data such as
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the gating mechanism of TZ in cellular models such as RPE1 or cultured dopaminergic neurons by immunofluorescence microscopy. You will also build and test TZ-derived molecular prosthetics with the aim
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project that combines cutting-edge approaches including state-of-the-art imaging techniques, pluripotent stem cell models, in vivo mouse models of neurological disorders, drug (brain) delivery and nanobody
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live in. Your role The CLAIM and ICR groups are seeking an outstanding postdoc to strengthen their research teams with expertise in Large Language Models, more precisely in Agentive Reasoning and LLM