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reconstitution, cell biology, and fluorescence microscopy imaging tools, we aim to uncover how protein-membrane interactions promote membrane microdomain formation and how these structures respond to external
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conditions (around 0.1 au from the Sun). By combining high-resolution remote sensing data (especially EUV spectral imaging) with advanced simulations, RIB-Wind seeks to more accurately characterize the solar
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for separately, please see: https://www.helsinki.fi/en/research/doctoral-education/the-application-process-in-a-nutshell . For more information on degree requirements and the application process, please visit
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to pursue a doctoral degree at the University of Helsinki, it must be applied for separately, please see: https://www.helsinki.fi/en/research/doctoral-education/the-application-process-in-a-nutshell . For
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recruitment portal. Further information about the position can be obtained from Tommi Jauhiainen (tommi.jauhiainen(at)helsinki.fi ). Additional information about the recruitment process can be obtained from HR
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daria.krivonos(at)helsinki.fi . If you have any questions, need assistance, or require accommodations during the recruitment process, please contact HR Specialist Minna Toivonen hr-sskh(at)helsinki.fi – we
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Grant, focusing on the development of novel deep learning tools to recommend reaction conditions for the synthesis of novel TRPA1 inhibitors. The project “A machine learning approach to computer assisted
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learning tools to recommend reaction conditions for the synthesis of novel TRPA1 inhibitors. The project “A machine learning approach to computer assisted drug design” is led by Docent Juri Timonen