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Centro de Estudos Filosóficos e Humanísticos (CEFH) | Universidade Católica Portuguesa | Portugal | 8 days ago
matrix, and study of relevant indicators related to student well-being and academic performance. Development and implementation of methodologies to support teachers in carrying out activities that promote
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development of new food products. In addition, it offers industry services related to the areas of nutrition, dietetics, and food in general. Where to apply E-mail fgarciamate@unav.es Requirements Research
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working with dr.Rudy Helmons (dredging, marine minerals) and dr. Austin Kana (design methodology, complex systems), where you will work on the development of an assessment framework to identify Best
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(Fixed-term and full-time for 2 years). Your future tasks Developing critical research pertaining to the impact of digital technologies on politics (broadly defined) (ideally country- or region
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guidance if required. They will be expected to take an active role within the research group, including assisting in the development of graduate student research skills as well as participation in and
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Helmons (dredging, marine minerals) and dr. Austin Kana (design methodology, complex systems), where you will work on the development of an assessment framework to identify Best Available Technology (BAT
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species providing the data foundation for adverse health effect risk assessment Assess hot spots in the Arctic of chemicals in local communities and exposure assessments Assess food web dynamics in relation
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+ communities based in or rooted in Southern Europe. Collect and analyze high-quality data, both on digital platforms and offline. Develop your own research questions within the framework of the project
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of areas including strongly correlated fermion materials, high-temperature superconductivity, topological electronic states of matter, developments and applications of computational methods
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on developing new methods for color-specific conditional generation in multi-modal generative models. The candidate will work on exploiting the intrinsic knowledge about color within text-to-image (T2I) models