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models, which are essential for understanding climate change impacts. The work involves reviewing existing modeling and model–data fusion techniques, and developing faster, machine-learning–based tools
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. • Demonstrated industrial-related experience. • For those that hold a PhD, a minimum of 3 years of relevant industrial experience is preferred. Required Knowledge, Skills, and/or Abilities • Ability to teach all
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imaging and machine learning. The main task of the successful candidate will be to help redefine certain traditional criteria of comparative anatomy used in archaeozoology and to establish new criteria
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at TalTech´s web-page: https://taltech.ee/en/phd-admission The following application documents should be sent to tarmo.soomere@taltech.ee CV Motivation letter Degree certificates as required by the university
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physical models. As the PhD researcher on this project, you will work at the intersection of machine learning, geometry processing and industrial simulation. You will have the opportunity to explore
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attacks in federated learning. Experience should be demonstrated by participation in projects in this area and scientific publications. Already enrolled in a PhD programme. Minimum requirements: Knowledge
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biological environments - Experience using machine‑learning algorithms for luminescence signal analysis and sensing applications - Experience writing scientific articles and presenting results at conferences
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, proteomics, metabolomics), Capacity to develop and/or apply : Statistical or mathematical models Machine learning / AI methods Systems biology modeling approaches Research position The fellow will conduct
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through external grants or other mechanisms. External funding is also expected to support student research and experiential learning opportunities. The specific appointment split will be determined based
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projects and deliverables May supervise undergraduate students working on the AI/ML projects QUALIFICATIONS PhD (or equivalent) in Machine Learning, Computer Science/Engineering, Biomedical Engineering, or