170 evolution "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" "UCL" "UCL" "UCL" "UCL" positions at DAAD in Germany
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Description We invite applications for a fully funded PhD position within the DFG Priority Programme SPP2389. https://tu-dresden.de/mn/biologie/allgemeine_mikrobiologie/spp2389?set_language=en
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academic environment. Required Documents Required Documents CV Certificates Transcripts Language certificate Motivation letter References Application Application https://www.frankfurt-school.de/en/home/study
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courses or doctoral candidates Selection Selection is made by the National Science and Technology Council - NSTC Further information National Science and Technology Council - NSTC https://www.nstc.gov.tw
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the development and application of probabilistic inference methods and machine learning techniques for quantitative uncertainty modeling and for the integration of heterogeneous climate data
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position is the development of novel machine learning methods for modeling molecular properties, in particular regression models for bi-molecular properties. The research is embedded in the thematic context
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/ Argentina https://www.argentina.gob.ar/educacion/campusargentinaglobal Alearg E (pasantías): Estudiantes de Ingeniería
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applies), preferably via the TUD SecureMail Portal https://securemail.tu-dresden.de by sending it as a single pdf file to mlcv at tu-dresden.de or to: TU Dresden, Chair of Machine Learning
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methods for photocatalytic membrane development. The project will focus on i) photocatalyst selection, looking beyond the most commonly used materials, ii) exploring options of catalyst deposition and
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(0054 11) 5371 5620 fax: (0054 11) 5371-5626 E-Mail: internacionales@rec.utn.edu.ar https://www.utn.edu.ar/es/secretaria-rrii/srrii-utn-daad Contact and Consulting Information and advisory centres
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: Development of machine learning algorithms for the localisation of seismic sources (e.g., on 2D grid maps) Analysis and preprocessing of large DAS datasets Use of synthetic training data from seismic