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record relative to career stage Excellent written and spoken English communication skills Following qualifications will be considered as an advantage: Experience with explainable AI methods Experience with
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highest level of general business knowledge, normally acquired through attainment of a directly job-related terminal degree or equivalent formal training in a recognized field of specialization that is
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animal species, generating standardized data that works effectively across diverse languages and cultural contexts while eliminating traditional barriers of recall bias. These methods are being deployed in
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sovereignty, relationality & research development, fieldwork & braiding knowledges, formal & informal science education, storywork & knowledge mobilization, training scientists, and policy & government agencies
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discipline. The candidates will have expertise in computational imaging, with: (i) an algorithmic focus, with particular interest in methods at the interface of deep learning and optimisation theory, and/or
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, Indigenous, and people of color, those with disabilities, those who are first generation, veterans, and those from 2SLGBTQIA+ communities. The postdoc will be formally mentored by Dr. Xiao Zang and will engage
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record in mentoring education research arcs, outstanding teachers, and careers in surgical education. The fellowship consists of extensive opportunities in education research, formal training in grant
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10.08.2021, Wissenschaftliches Personal Positions in the Formal Methods for Software Reliability group of TU Munich led by Prof. Jan Kretinsky: - postdoc in the area of quantitative verification