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Field
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conducting empirical studies in higher education and coordinating data collection; examining teaching practices informed by Universal Design for Learning, the sensory environment and social inclusion
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of application: Klinik für Kardiologie, Angiologie und Pneumologie Location: Heidelberg Job Category: Science and teaching Working hours: Part time (65 %) Published: 01.07.2026 Limitation:Temporary (4 years
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Inria, the French national research institute for the digital sciences | Villeurbanne, Rhone Alpes | France | about 1 month ago
, and perform actions on behalf of users. These capabilities create opportunities in areas such as personal assistance, healthcare, software development, mobility, supply-chain optimisation and resource
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, to acquire new knowledge about research tasks. Where to apply Website http://www.ub.edu/caiac/solBeca?idConvocatoria=50563 Requirements Research FieldPharmacological sciencesEducation LevelMaster Degree
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light of technological advances in digital tools and resources, as well as the ongoing migration crisis, WP4 reconsiders the main concepts and approaches to language learning and teaching: it investigates
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worlds. You will design QEC codes suited to realistic hardware, develop the decoding algorithms that make them practical, and map the trade-offs between reliability, qubit overhead and decoding latency. A
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! Education Master's degree (or equivalent) in cell biology, toxicology, molecular biology, biochemistry, biomedical sciences, or a closely related field. Experience and skills • Knowledge of or experience in
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PhD thesis. To be eligible for this position, applicants must meet the Marie Skłodowska-Curie admission requirements: You must not already hold a doctoral degree. You must comply with the MSCA mobility
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will receive: (i) a competitive living allowance (salary), a mobility allowance and a family allowance (if qualified); (ii) two funded 3-month secondments in the industry in TDC NET (Denmark) and Dell
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goal of your PhD project will be to develop combined X-ray and visible-light imaging technologies and machine learning methods for high-throughput inspection tasks. The work will include the development