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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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. Knowledge on multiphase (gas-particle two phase system), thermal energy storage, and/or renewable hydrogen technologies. Familiar with application of machine learning and deep learning algorithms to fluid and
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at Aalto University (https://into.aalto.fi/display/endoctoralsci/How+to+apply#Howtoapply-Eli… ) a Master’s degree in Artificial Intelligence, Machine Learning, Computer Science, Cognitive Science
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) platforms used in machine learning, big data and artificial intelligence (AI) based applications (CPUs, GPUs, AI accelerators etc.) require high power demands with optimized power distribution networks (PDNs
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Robotisation (PROMAR) group, headed by Matthias Rupp. The group develops fundamental and technological expertise in machine learning for materials science, including data-driven accelerated simulations and
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strong research capabilities with a deep understanding of trading to design, validate, backtest, and implement statistical and advanced machine learning models. Your work will span a range of initiatives
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University explores synergies between nonlinear control theory and physics informed machine learning to provide formal guarantees on performance, safety, and robustness of robotic and learning-enabled systems
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Liverpool where, in the School of Computer Science and Informatics, we have an active group of PhD students, postdocs, and academics working at the intersection of Machine Learning, Verification and
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from visual and auditory cortices recorded over multiple days Apply and adapt advanced machine learning frameworks (SPARKS and CEBRA) for supervised and unsupervised analysis of high-dimensional neural
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data science and machine learning Additional software skills such as Shiny, LaTeX, Tidyverse, Tableau, C/C++, Java, GitHub Experience in report writing for projects underpinned statistics Attributes and