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de Madrid, the Healthcare Advisory Council of the Community of Madrid and the Foundation for Biomedical Research of Hospital Universitario La Paz, which will be the managing body of the Institute
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communities; 2. Body, gender and identities; 3. The city, mobility and urban sustainability. Each of these project areas studies two intertwined domains: 1) Local communities and social movements as
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programming (Python, MATLAB), neural networks, deep learning or physiological signal analysis. - Minimum of 2 years of accredited professional or research experience in tasks directly related to: AI algorithm
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into the network led in 2017 to the detection of a neutron star binary merger that could be followed in electromagnetic signals, representing the beginning of multi-messenger astronomy. At the moment, LIGO and Virgo
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into the network led in 2017 to the detection of a neutron star binary merger that could be followed in electromagnetic signals, representing the beginning of multi-messenger astronomy. At the moment, LIGO and Virgo
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networks. Community manager. − Collaboration in the preparation of reports and other CITEEC documents/regulations: content, editing, layout, translation... − Collaboration and support in the organisation
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, the Healthcare Advisory Council of the Community of Madrid and the Foundation for Biomedical Research of Hospital Universitario La Paz, which will be the managing body of the Institute. This strategic alliance has
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. Supervise postdoctoral researchers, PhD students, and laboratory technicians. Participate in international cancer research networks to position the group on the biomarker research map. Publications and
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speech (i.e., statistical learning), we aim to understand the neurophysiological underpinnings of the beneficial effects of music exposure across early language acquisition. The underlying neural network
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personalized research projects under senior supervision (2) Exchanging knowledge with the scientific community and the general public (3) Network-wide training in theory and methods (4) Complementary training