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expertise in the RTG-addressed PhD subjects, high interdisciplinary desire to learn and willingness to cooperate, very good verbal and written English communication skills as well as the absolute
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 16 days ago
will develop computer vision, machine learning and control algorithms for a robot to perform packaging tasks. Human demonstrations will be used to generate data for learning. These data will encompass
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been revolutionized in recent years by machine learned interatomic potentials (MLIP), and questions that were impossible to tackle five years ago can now be addressed. The state-of-the-art approach
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PhD students in total. The aim of LowDataML is to train a new generation of scientists at the interface of machine learning, chemistry and other fields. Project tasks: We propose a data science guided
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Scene Understanding Detection and Identification of Objects (SSUDIO) project. The purpose of this project is to develop scene understanding from 3D scans of ships by applying machine learning/computer
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description The project will use bioinformatic analysis together with comparative approaches to individual cells, and machine learning to investigate how the vertebrate head evolved and what mechanisms control
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, for their analysis and optimization, we use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our activities
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Medical - Clinical Medical - Research Internal Number: A-179907-11 General Description The laboratory of Gislin Dagnelie, PhD, Lions Vision Research and Rehabilitation Center, Johns Hopkins Wilmer Eye
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available1Company/InstituteFaculty of Mathematics and Computer ScienceCountryPolandGeofield Contact City Lodz Website http://iso.uni.lodz.pl/ Street Narutowicza 68 Postal Code 90-136 E-Mail sekretariat
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simulations, machine-learned force fields, and artificial intelligence (AI). The successful candidate will lead the development of a computational platform that unifies first-principles methods, classical