34 parallel-processing-bioinformatics research jobs at AALTO UNIVERSITY in United Kingdom
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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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consideration. Applications will continue to be processed and reviewed following this date until the position is filled, but candidates are encouraged to apply as soon as possible. Please write your application
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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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interaction. Programming skills needed to do data analysis (we mainly use Python) You can be interested either in theoretical methods development or applications, or a bit of both Interest in working on a
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on the utilization of renewable resources. Bio2 aims to contribute to the development of novel solutions to move towards sustainable primary production and processing systems that can produce materials with fewer
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(at)aalto.fi. In any question regarding the recruitment process, please contact HR Advisor Monika Mäkinen, hr-elec@aalto.fi . About Aalto University and Finland The Department of Electronics and Nanoengineering
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through long-term impact assessment and optimization. The goal is to develop a framework to estimate carbon emissions across AI's development, operation, and use. This framework enables stakeholders
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through long-term impact assessment and optimization. The goal is to develop a framework to estimate carbon emissions across AI's development, operation, and use. This framework enables stakeholders
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related to the application process: hr-arch@aalto.fi We will review applications as they arrive and may invite suitable candidates for interviews during the application period. You will hear from us no
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on the development of a computational setup for fiber-enriched materials design within the Processing-Structure-Properties-Performance (PSPP) framework under the joint supervision of Assistant Professor Sergei Khakalo