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Job Description FACULTY OF ARTS AND SOCIAL SCIENCES ACADEMY OF WELLNESS AND HUMAN DEVELOPMENT Research Fellow / Senior Research Associate (24250392) The appointee is expected to conduct cognitive
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learning in context. Our research examines mechanisms of human learning, the conceptual structure of human knowledge, how people communicate expertise, and effective strategies when trying to build new
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Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial | Portugal | about 3 hours ago
Qualifications: Bachelor’s degree in Mechanical Engineering Proficient knowledge of the finite element method for structural analysis using Abaqus® software Advanced knowledge of programming languages such as
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the application which project you are specifically interested in. Further details on the projects can be found here: https://www.fz-juelich.de/en/jcns/careers/fellowships/tasso-springer-fellowship-program Your
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, progression, and therapeutic response. This research is fundamental to advancing our knowledge of cancer and improving patient outcomes. See further information at the lab webpage: https://odin.mdacc.tmc.edu
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objective of generating novel knowledge about how to reduce social inequality. The interdisciplinary center integrates researchers with substantive expertise from education, psychology, sociology, economics
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Alzheimer’s disease to the study and for administering non-invasive brain stimulation (phase-locked TI electric fields and audio), electroencephalography (EEG), and cognitive paradigms during wakefulness and
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skills and advanced knowledge of signal analysis; Proven laboratory experience, specifically in microscopy techniques and cell culture. Preferential: Preference will be given to candidates interested in
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theory as well. Knowledge of and working experience with modern exact methods such as AdS/CFT integrability, conformal bootstrap or localization will be considered an advantage. Further information
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Computer Science, Computer Science and Engineering or related area. Additional optional skills and qualifications: Proven track record in ontology alignment, machine learning with biomedical data, and knowledge