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datasets with new products and when existing products change during operation The Doctoral Researcher is expected to focus on research on applying offline reinforcement learning to heavy machines. While
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) For questions 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
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science, or human-computer 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
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an extensive network of scientific contacts. This includes contacts to the Aalto startup scene and community. A way to be close to the research process while focusing on interesting computational problems and
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University. For more information on the general requirements and the application process for doctoral studies, please visit https://www.aalto.fi/en/doctoral-education/how-to-apply-for-doctoral-studies What we
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period, reopen the application process, and to consider candidates who have not submitted applications during the application period. Further information Professor Sebastian Szyller, e-mail "seb.szyller
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the impacts of the characteristics in different scales of the investigated processes on their overall techno-economic-environmental-energy efficiency. This is an interdisciplinary project requiring expertise in
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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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, and artificial intelligence meet to address complex environmental challenges. About the Project The Adaptive Design for AI-Driven Processes in Transforming Dynamic Landscapes (ADAPT) project develops
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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