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Field
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-antigen triggers of regulatory T cells in the context of Multiple Sclerosis (MS). This position is part of a large multidisciplinary collaboration between the University of Oxford, University of Cambridge
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-motivation and ability to work on projects independently; proven ability to handle multiple projects concurrently and meet deadlines; and demonstrated proficiency in Python and willingness to contribute
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and have strong computational biology skills. Previous experience with epigenome-wide assays is preferred. The successful candidate will be working in a collaborative environment with multiple faculty
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scale and resolution. This ambitious project spans multiple institutes including the Wu Tsai Neurosciences Institute, Stanford Bio-X, and the Human-Centered Artificial Intelligence Institute, bringing
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attributes; a) familiarity with the physical processes contributing to sea level change; b) experience with ocean and/or earth system modeling; c) experience with Python and scientific data analysis.Candidates
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closely with scholars in the humanities, historians, ethicists, legal scholars, and policy advocates. Within NetSI, our team collaborates with multiple research groups working on questions of public health
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at multiple fidelities: from simplified beams to full 3D FE models. You will collaborate closely with both academic and industrial partners in Denmark and abroad, ensuring that your research has impact in
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, equitable, trustworthy, and context-sensitive. Multi-agent architectures where multiple AI systems collaborate, negotiate, and adapt to model complex human learning processes and support group work
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at top-tier conferences (MICCAI, NeurIPS, IEEE IROS, IEEE VR), winning multiple best paper awards. Recent achievements include award-winning synthetic data generation with diffusion models, and high
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, using R or Python; experience with these datasets is helpful but not required Preparing statistical reports and presentations Presenting findings at regional or national scientific meetings Mentoring