40 parallel-processing-bioinformatics positions at AALTO UNIVERSITY in United Kingdom
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Project The Adaptive Design for AI-Driven Processes in Transforming Dynamic Landscapes (ADAPT) project develops scalable, data-driven design methodologies that transform dynamic environmental processes
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device nanofabrication and clean room processing of 2D materials (required). Skill sets of handling low-temperature and ultra-high vacuum systems, such as molecular beam epitaxy (MBE) or STM experience
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additional information on the position, kindly contact prof.Olli Varis (olli.varis@aalto.fi ). For more information on the process, please contact ENG HR Team (hr-eng@aalto.fi ). About Finland Finland is a
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flexibility depending on interests and experience: Design and simulation of III-V lasers and PIC architectures III-V (mainly GaAs) fabrication process development in the cleanroom Assemble and use custom test
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Mika Järvinen (+358 50 414 2993, mika.jarvinen@aalto.fi). For questions related to the application process, please contact Anna-Maija Harju (anna-maija.harju@aalto.fi ). We will go through applications
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mechanical oscillators can be utilized for fundamental studies probing quantum mechanics in massive systems, as well as for applications in quantum information processing. The measurements are carried out
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(matti.kuittinen@aalto.fi ). For questions related to the application process, please contact HR Partner Enni Ailoranta hr-arch@aalto.fi . We will go through applications, and we may invite suitable candidates
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relating to the recruitment process please contact HR Partner Heli Solla (heli.solla@aalto.fi). How to apply The application materials for the lecturer position include: If you want to join our community
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webpage for open positions). If you wish to hear more about the position, you can contact Associate Professor Pekka Malo (pekka.malo@aalto.fi ). In questions related to the recruitment process, contact HR
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Project The Adaptive Design for AI-Driven Processes in Transforming Dynamic Landscapes (ADAPT) project develops scalable, data-driven design methodologies that transform dynamic environmental processes