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graduate and/or post-graduate experience in time-resolved X-ray experiments and a proven record of accomplishment within state-of-the-art simulation and analysis of such data sets. We are looking for a
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record of scientific productivity. Previous experience in metabolomics, computational biology, and/or hematology-oncology is strongly preferred. Interested individuals should send a CV, a short summary of
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. The candidate will have the opportunity to obtain additional external funding and develop an independent research program during the postdoctoral training. We are looking for an enthusiastic scientist with a
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submitted your application, you must send this person’s details (name, job title, place of work, and email address) as well as the name of the position you have applied for to: HR.Nattech@au.dk Formalities
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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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single-cell genomics, epigenetics, and imaging technologies with computational approaches to unravel the mechanisms of immune cell fate decisions in health and disease. As a postdoctoral researcher, you
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of heart disease Your studies will take advantage of in vitro and in vivo pre-clinical models, including hiPSC-derived systems The postdoctoral project will combine experimental (wet-lab) and computational
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A postdoc position in the Torben Heick Jensen lab, Aarhus University, Denmark: Mammalian Nuclear ...
computational biologists aiming to examine the factors and complexes governing the production and turnover of eukaryotic transcriptomes. The postdoc will be affiliated to the Department of Molecular Biology and
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. The carbon capture pilot is envisioned to include pre-treatment and post-treatment steps, enabling flexibility and optimization of the carbon capture process for its practical application. The position is
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computational models to map co-expression networks and predict systemic disease transitions. Characterise intestinal microbiome changes and their correlation with inflammatory diseases. Computational modelling