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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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                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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                the selection process, consideration will be given to the applicant’s research plan, previous academic performance, international orientation, research merits, the duration and progress of any previous funding 
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                as well as the reactor and process simulation and analysis. Details will be adjusted collaboratively as the project progresses. The project has access to two experimental reactor setups, common 
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                received before September 29th 2025 (23:59 EET (GMT+2)) will be given guaranteed consideration. Applications will continue to be processed and reviewed following this date until the position is filled, but 
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                field. Existing skills and knowledge in electronic device nanofabrication and clean room processing of 2D materials (required). Skill sets of handling low-temperature and ultra-high vacuum systems 
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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 
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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