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the following areas desirable but not essential: electrocatalysis, rheology, coating technology, machine learning Intrinsic motivation to show initiative, creativity, and to work independently Excellent
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the HNSCC team, including Taran Gujral (machine learning-enabled drug screening), Slobodan Beronja (mouse models of HNSCC), and Patrick Paddison (functional genomics). This work will encompass a broad array
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information, quantum technologies and machine learning. Internal further training & coaching: The Vienna Doctoral School as well as the Department of Human Resources offer plenty of opportunities to grow your
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University of North Carolina Wilmington | Wilmington, North Carolina | United States | about 20 hours ago
Posting Details Posting Details Position Title Lecturer - Reading/Literacy in the Department of Early Childhood, Elementary, Middle, Literacy, and Special Education External Link to Posting https
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effective implementation of assessment priorities. This position collaborates with internal stakeholders on assessment and accreditation. How to Apply: Interested candidates may apply online at https
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, software and data engineering, data mining, machine learning, and Artificial Intelligence. Qualified candidates are invited to submit their applications through the web portal available at https
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25th February 2026 Languages English English English The Department of Materials Science and Engineering has a vacancy for a PhD Candidate in machine learning and large language models (LLMs
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SFI FAST: PhD position in Microstructure/texture evolution during extrusion of scrap-based Aluminium
(as machine learning techniques, etc.). Personal characteristics In the evaluation of which candidate is best qualified for the PhD position, emphasis will be placed on education, experience and
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-based transfer learning classification model for two-class motor imagery brain-computer interface. International Journal of Neural Systems (IJNS). https://doi.org/10.1142/S0129065719500254 * Kudithipudi
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disciplines such as neuroscience/cognitive science, AI and machine learning, robotics, engineering, computer vision, and signal processing. Details of this year’s workshop are at https://sites.google.com/view