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on: https://www.dges.gov.pt/pt/pagina/reconhecimento Workplan and the objectives to achieve: The workplan proposed comprises two topics, each to be tackled by each studentship offered: Topic 1 - Automatic
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | about 23 hours ago
expected to develop and run workshops to introduce your work to end users. For further detail on the Lanfear Lab, our ideals and goals please visit our webpage: http://biology.anu.edu.au/research/labs
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- Association for Research and Development of Sciences at https://fciencias-id.pt/ . Time limits for the appeal procedure: In case of negative decision, the candidates have 10 business days, after the date
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type. The fellowship is due to start in April 2026. . WORK PLAN: The aim is to support research and development work on mechanisms and proofs of concept that allow the integration of a digital
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health sciences across the campuses of Johns Hopkins University to foster innovative, interdisciplinary scholarship and to train undergraduates, graduate students, and health professionals with skills
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require development of advanced experimental and data analysis skills and will work closely with the Doctoral candidate working in Cambridge on data assimilation (https://www.imft.fr/dc10-arterial
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position. We are most interested in applicants who have experience in computational methods development, in human genetics or a different field. Possible areas of research include: 1. Developing methods
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advertised on Sorbonne Université’s website: https://www.sorbonne-universite.fr/en/news/msca-postdoctoral-fellowships-sorbonne-university-2026 2. Prepare your CV, a motivation letter and fill in the required
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at Harvard Medical School in Boston, Massachusetts. The work of the Gygi lab is focused on developing and applying mass spectrometry-based approaches to the drug discovery pipeline. We welcome applications
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in the 2025 QS World University Rankings by Subjects. We are hiring a Research Fellow in Signal Processing and Machine Learning to develop signal processing and machine learning algorithms and methods