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Field
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of backgrounds and perspectives. For more information, please visit the WTI website: https://wti.yale.edu . Qualifications Applicants must have a PhD (or equivalent) at time of hire. Current Yale
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implementation of empirical studies with human participants. Strong analysis skills, including both quantitative and qualitative methods. Strong background in computational methods, especially for working with
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learning, with the objective of designing new learning paradigms where synthetic data is generated dynamically to enrich and optimize training datasets. The project focuses on human-centered computer vision
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is found. The successful candidate will develop and apply computational approaches to biochemical datasets, with artificial intelligence/machine learning (AI/ML) being a major focus. Many of
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physical sciences, teaching classes for the 1st cycle and 2nd cycle studies for the following degree programmes: Physics and/or Applied Computer Studies and/or Computer Studies and/or Data Science and
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, ROS) Solid skills in numerical analysis Advanced knowledge of computer vision Experience in human–robot interaction Particularly Meritorious It is particularly meritorious if the applicant has: A PhD
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analysis. Familiarity with research documentation maintained according to ISO standards. Experience using AcqKnowledge software. Willingness to acquire skills in machine learning and artificial intelligence
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of Computer Science and Electrical and Computer Engineering. INESC-ID’s research impact is focused on four Thematic Lines Energy transition Life and health technology Security and privacy. Societal digital
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spans computational materials design, catalysis, energy materials, machine learning, and artificial intelligence. We offer a collaborative and international research environment with close interactions
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and qualifications A PhD degree in computational biology, machine learning, computer science, data science, bioinformatics, or a related discipline Demonstrated machine learning experience in form