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Two postdoctoral positions (3-year) in Experimental Evolution of Methanogenic Microbiomes in Bioe...
pipelines in bioelectrochemical reactors defining and comparing high-performance phenotypes comparative and functional omics of the communities linking genotype and function to system-level performance
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Postdoc position in method development in human statistical genetics, with a focus on classificat...
on a predictor X; candidates should understand how this function performs the analysis (e.g., estimates the effect size, assesses significance). Most likely, the applicants will have a BSC and/or PhD
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at the Department of Electrical and Computer Engineering, Aarhus University, where we are advancing communication-efficient and distributed foundation model inference across the computing continuum
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Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description AAU Energy invites applications for a full-time, two
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quantitative characterization of mixed defined microbial communities, including adaptive evolution. This project is a collaboration with chemists to produce high quality carbon materials from waste CO2 . Systems
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student mentorship, and strong interpersonal and communication skills. Documented ability to publish scientific work in high‑ranking journals. Responsibilities Conduct state‑of‑the‑art research within
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Job Description Migraine affects more than 15% of the global population and remains inadequately treated despite advances in biologics and receptor-targeting therapies. Emerging computational
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-bacterial electron transfer in these systems. By combining cultivation-based microbiology with electrochemical approaches and high-resolution imaging, the work will directly probe how energy metabolism is
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TIMSTOF OmniTrap MS Curate high-quality MS/MS datasets and perform detailed fragment ion interpretation Collaborate with computational researchers on downstream data interpretation and methodological
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at the Department of Electrical and Computer Engineering, Aarhus University, where we are advancing communication-efficient and distributed foundation model inference across the computing continuum