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, data mining, machine learning, natural language processing, human-centered computing, mobile and ubiquitous computing, cyber-physical systems, and engineering education. IST hosts the ABET-accredited BS
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specialised expertise in the Machine Learning for Engineering sub-theme. Candidates from all areas in machine learning are encouraged to apply, with a special focus on the areas of (i) information theory and
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in Estonia and Europe through competitive research grant applications, especially as a coordinator. Involving students (BSc, MSc, PhD) in research and development projects and supervising bachelor's
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. In addition to actively researching and publishing, the candidate will teach both graduate and undergraduate courses (typically six [6] courses per academic year) to cover curricular needs in both
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the application of these methods to problems in the physics of oxides, semiconductors, metals and their surfaces. Machine learning methods are used to close the complexity gap. Currently, the group consists
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that blend industrial design with advanced technologies. He/she will apply expertise in areas such as electronics/sensors technology, machine learning/programming, physical ergonomics/cognitive ergonomics
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Qualifications: A Master’s degree in an appropriate related scientific or engineering discipline and four (4) years of progressively responsible related professional research experience. A PhD in a scientific or
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, and Artificial Intelligence, in our West Lafayette and Indianapolis locations, as well as graduate MS and PhD programs. For more information, see https://www.cs.purdue.edu . Opportunities
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chemistry, from the use of advanced electronic structure methods to the development of dynamical approaches to study photochemical reactions, also including machine learning. The group is part of the Cluster
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, H-index and ORCID (see http://orcid.org/ ) Teaching portfolio including documentation of teaching experience Academic Diplomas (MSc/PhD) You can learn more about the recruitment process here