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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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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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to the University of Turku email tech-doc@utu.fi by 14 November 2025. A right to study is a prerequisite for an applicant to be chosen for a fixed-term doctoral researcher position. Instructions on how to apply
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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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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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a comprehensive multi-perspectives analysis approach, essential to track the impacts of the characteristics in different scales of the investigated processes on their overall techno-economic
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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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public events and assisting with research projects. Please send your application to riikka.rossi@helsinki.fi by October 20th, 2025 a cover letter stating your motivation to apply for the position and your
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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