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the ability to teach these courses effectively, drawing on research or applied expertise in areas such as comparative politics, international relations, political theory, political economy, or related fields
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functions to work properly. Please turn on JavaScript in your browser and try again. UiO/Anders Lien 1st March 2026 Languages English English English PhD Research Fellow in Deep learning for imaging of marine
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Kaunas Website https://en.ktu.edu/ Street K. Baršausko g. 59 Postal Code LT- 51423 E-Mail cv@ktu.lt STATUS: EXPIRED X (formerly Twitter) Facebook LinkedIn Whatsapp More share options E-mail Pocket Viadeo
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application (in German) including the salary can be found here: https://lfuonline.uibk.ac.at/public/karriereportal.details?asg_id_in=15623 The University of Innsbruck is committed to raising the quota of female
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of TechnologyCountryLithuaniaCityKaunasPostal CodeLT-51423Street K. Baršausko g. 59Geofield Contact City Kaunas Website https://en.ktu.edu/ Street K. Baršausko g. 59 Postal Code LT- 51423 E-Mail cv@ktu.lt STATUS: EXPIRED X (formerly Twitter
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The Franciszek Górski Institute of Plant Physiology Polish Academy of Sciences | Poland | about 11 hours ago
Applicants must: hold a PhD degree in biology, agricultural sciences, biotechnology, bioinformatics or a related field, have experience in laboratory work, be willing to learn and apply new laboratory and
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. Additionally, doctoral candidates will take basic courses consisting of two main sections each: E-learning courses covering the essentials Cognition academies (classroom weeks) in which all doctoral candidates
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perturbation modelling. The ideal applicant brings not only strong technical skills, but also interdisciplinary knowledge on the subject. More precisely: PhD degree in computer science, machine learning
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recently funded centre of excellence (Integreat). Integreat collects scientists from statistics and computer science and offers a flourishing machine learning community, including many PhDs and PostDocs
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minimizing computational and energy costs. The proposed approaches will rely on machine learning methods applied to image analysis, with the objective of enabling early identification of at risk areas and