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of artificial intelligence, aesthetics, history of philosophy, epistemology, philosophy of mind, metaethics, metaphysics, normative ethics, political philosophy, philosophy of language, applied ethics, and
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This postdoc position is a full-time temporary employment for two years. Application Procedure Please submit your application in English as PDF files according to the instructions below. Each file should not
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at Chalmers. Application procedure The application should be written in English and be attached as PDF-files, as below. Maximum size for each file is 40 MB. Please note that the system does not support Zip
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of support for the recruiting process in connection with this position. *** Chalmers University of Technology in Gothenburg conducts research and education in technology and natural sciences at a high
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/forskarutbildning/ Application process Applicants are expected to submit their application in English, which should include: - A personal letter which states the reason for being interested in the position and in
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on the circularity of construction materials for the benefit of the environment, economy and the natural resources. This position focuses on identifying challenges and opportunities related to circularity of materials
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and similar substances interact with biological systems. By investigating how such substances affect molecular targets and induce changes in cellular and physiological processes or pathological
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beamline is dedicated to X-ray absorption spectroscopy (XAS) and X-ray emission spectroscopy (XES) experiments in the medium and hard X-ray energy range, 2.4 - 40 keV. The beamline is in user operation since
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with infrastructure. Awareness of the needs in processing and handling of sensitive data. Excellent oral and written communication skills. Ability to convincingly convey the excitement and impact of a
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to the application deadline. PhD in computer science, electrical engineering, biomedical engineering, or a related field. Experience in Python programming, natural language processing, and multimodal deep learning