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special light-switchable organic molecules that mimic the function of biological systems. These synthetic "molecular machines" will be composed of various photoswitches and molecular motors, with
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-memory computing. University: Faculty of Chemical Engineering, UCT Prague; Faculty of Science, Charles University Group: Lubomír Rulíšek Group, Theoretical Bioinorganic Chemistry Tutor: Doc. Mgr. Michal
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, Molecular analysis of growth regulation in animals Tutor: David Sabatini,MD/PhD Field of study: Biochemistry, Cell biology, Biology How to apply: At the Institute of Organic Chemistry and Biochemistry
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chemistry and accurate machine-learned oligopeptide potentials with applications in structural and evolutionary biology. First, we will develop a new computational tool, denoted as QMLFold. This would allow
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few years have focused on the generation of machine-learning force fields for biological molecules, such as SpookyNet or AI2BMD. These offer the accuracy of quantum-chemical methods with many orders
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member (more than 90 days), pre-certification training, or military service. At least one scholarly publication indexed in the Thomson Reuters Web of Science or Scopus databases within the last three years
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computer models of various ribosomes or their parts, perform large-scale computer simulations of them, and analyze the simulations using state-of-the-art statistical models and machine learning. He or she
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computer models of various ribosomes or their parts, perform large-scale computer simulations of them, and analyze the simulations using state-of-the-art statistical models and machine learning. He or she
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-distance-energy data coming from Scanning Probe Microscopy on surfaces relevant for life sciences research and medicine, including curve classification tools based on machine learning, providing both
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methods of detection, identification, classification and tracking of objects of different sizes, shapes and speeds of movement using elements of artificial intelligence and machine learning. • Research work