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from the School of Physical and Mathematical Sciences with the School of Chemical and Biomedical Engineering. It is jointly run by the College of Science and the College of Engineering (https
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, demonstrated research ability, and strong communication skills. The successful candidate will conduct original research on core problems in biodiversity, foster interactions within the Centre, run a seminar
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opportunities for improving data quality and research methodology. Extract data from research sources and enter it into SSLA databases related to corporate and securities litigation. Conduct statistical analyses
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to provide effective teaching and carry out research in collaboration with members of members of one of our research groups. See our web page https://math.ua.edu/research-overview/ for more information
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Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial | Portugal | 4 days ago
Python or others (Essential) Basic knowledge of the mechanical behaviour of composite materials Experience in writing technical reports, scientific papers, or project documentation Initiative, sense
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biomarkers for early detection, risk stratification, and treatment response, and by exploring new therapeutic strategies to improve patient outcomes. For more details, please view https://www.ntu.edu.sg
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models Model human alignment, relating model behavior to behavioral (and potentially neural data) data The overarching goal is to produce rigorous, high-impact work that treats language models as
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wording. https://diariodarepublica.pt/dr/legislacao-consolidada/lei/2004-58216179 Regulations for Research Grants of the Foundation for Science and Technology in force https://diariodarepublica.pt/dr
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School of Nursing and Midwifery. The role involves working on high-impact data linkage project linking the NICPR and the Northern Ireland Longitudinal Study (NILS). The role's primary purpose is to conduct
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research position under the supervision of Dr. Chris Smith Home | Chris Smith . The lab— in the Evolution, Ecology, and Behavior section—investigates machine learning approaches for spatial population