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the SFF Integreat, The Norwegian Centre for Knowledge-driven Machine Learning (ML) , a centre of excellence funded by RCN and in operation until 2033. The project PI and team are also in close collaboration
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during sitting, walking, running or performing sports; or (ii) generative machine-learning models for physiologically realistic avatar construction from image or point-cloud data. Qualifications
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completed a Master’s degree (120 ECTS) or equivalent in in Demography, Economics, Sociology, Health Economics, Psychology, or other relevant field of study. Grade point average of A or B on the ECTS scale in
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responses and recovery in humans. To this end we combine data from psychopharmacological experiments in healthy participants and real-world clinical data from surgery patients for a more in-depth
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healthy participants and real-world clinical data from surgery patients for a more in-depth understanding of stress and resilience mechanisms. The project is an interdisciplinary effort bridging psychology
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placed on academic qualifications, the candidate’s motivation, and personal suitability. Interviews will be performed as part of the selection process. Application with attachments must be submitted via
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normal processes, provide insight into mechanisms that cause illness, and promote good health. The Institute is responsible for teaching in basic medical sciences for the programmes of professional study
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knowledge in order to understand normal processes, provide insight into mechanisms that cause illness, and promote good health. The Institute is responsible for teaching in basic medical sciences
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experience with mental health research is an advantage. Proficiency in executing computationally intensive analyses on high-performance computing systems, including job scheduling, parallel processing, and
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(Vietnam). The focus on products and processes may also lead the project to other Southeast or Northeast Asian countries. The full project description can be provided upon request, please contact project