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Field
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bioinformatics tools for integration of multi-omics and gene regulatory networks. The long-term research goal is to answer the key scientific question “How non-coding genetic variant act through context specific
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synthesize complex, bioactive small molecules, as well as how these molecules function in nature and in the context of human health. We are looking to hire postdoctoral fellows that share this interest in
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context. In addition to carrying out translational research with these microphysiological models, the successful candidate will be expected to apply for fellowship funding, contribute to the writing
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on concepts and content Presenting your research work in the context of academic teaching and to the general public You will have: A university degree in history or a related discipline An excellent doctorate
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the context of the geophysics, geochemistry and dynamics of the terrestrial planets. What distinguishes this approach is its focus on post-giant-impact systemwide dynamics, and the exchanges between planets
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scheduled offshore research cruise in July 2026. Will bring experience conducting and interpreting stable isotope analyses in ecological contexts Has experience working with marine field samples or at-sea
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, or geographical barriers. As part of our commitment to excellence in research and professional practice in academic contexts, we are proud to provide our staff with access to world-class facilities and equipment
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Life and Health Sciences Research Institute (ICVS), from the School of Medicine (EM) of the University of Minho | Portugal | 5 days ago
which the present research fellowship is part of focuses on the identification and validation of Sporothrix brasiliensis sialidase-1 inhibitors in the context of developing innovative therapeutic
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experience or emerging expertise in the Scholarship of Teaching and Learning (SoTL) Teaching experience in higher education or graduate-level contexts Demonstrated ability to manage multiple projects and
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libraries (e.g. Python, TensorFlow/PyTorch, Scikit-learn) Demonstrated experience in applying machine learning or data-driven methods to physical systems, preferably in the context of fusion research Proven