154 data-"https:"-"https:"-"https:"-"https:"-"https:"-"LGEF" Postdoctoral positions at Nature Careers
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(e.g. RNAi, CRISPR/Cas9, small-molecules). In this context, we also develop new computational tools for automated analysis and data visualization. These include algorithms and software applications
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, interests, and career goals align with its objective PhD diploma or a letter/information indicating the expected defense date Transcript of all modules and results from university-level courses taken List
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to conferences For more information concerning this position, please contact Prof. Bertinelli, email: Your profile We are looking for a candidate with a PhD in economics, preferably with a specialization in
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various disciplines: computer scientists, mathematicians, biologists, chemists, engineers, physicists and clinicians from more than 50 countries currently work at the LCSB. We excel because we are truly
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/information indicating the expected defense date Transcript of all modules and results from university-level courses taken List of publications Names and contact details of two academic referees Early
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to the advertised research topic and/or project, including how your background, interests, and career goals align with its objective PhD diploma or a letter/information indicating the expected defense date Transcript
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Aarhus University with related departments. Contact information Before applying or for further information, please contact: Associate Professor Aurelien Dantan, +4523987386, dantan@phys.au.dk . Deadline
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will be part of a research environment focusing on integrating multi-source satellite remote sensing data and developing novel algorithms to quantify agroecosystem variables for environmental
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innovative strategies to improve human health. HT is composed of five Centers: Health Data Science, Genomics, Computational Biology, Neurogenomics and Structural Biology. The Centers work together to enable
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Postdoctoral Researcher Position in Ecological Knowledge-Guided Machine Learning at Aarhus Univer...
on “Integrating AI into Aquatic Ecosystem Models to Decode Ecological Complexity” funded by Villum Fonden. Within that project, the focus is on exploring novel ways to infer information from environmental data