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Field
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-Gordon model, the scaling limit of the near critical Ising model, or the massive Thirring model. Qualifications We are looking for applicants with a PhD in mathematics or theoretical physics, with
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-computer interaction, social networks, fairness, and data ethics. Our research is rooted in basic research and centres on mathematical models of the physical and virtual world, as a basis for the analysis
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Preparation of results for publishing and presentation at conferences Development of models for health and environmental impact assessment Your profile We are looking for a candidate with: PhD in the area of
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delineation and improve the outcomes of SCC surgery. Job Responsibilities: As a PhD candidate, you'll focus on: Develop cutting-edge AI models: Train state-of-the-art deep learning models to segment SCC and
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; delegate tasks and establish priorities. Perform other duties as assigned. Knowledge – Skills – Abilities Core Scientific Knowledge: Biology Chemistry Mathematics Statistics Laboratory and Technical Skills
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to the comprehensive analysis of field samples and the mathematical modeling of cellular interactions. LPHI includes four teams working on parasite models (Toxoplasma and Plasmodium), thus offering a stimulating working
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master's degree (or equivalent) and PhD in Mathematics/Statistics/Data Science Research expertise in the analysis of complex systems Familiar with network analysis, concepts of resilience (e.g. adaptive
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novel mathematical approaches for mapping between distinct embedding spaces Supervise and mentor the PhD student Coordinate technical integration across multiple work packages Drive innovation in low
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/postdoctoral-researcher-in-oper… Requirements Specific Requirements Motivated researcher with a PhD degree in Operations Research, (Applied) Mathematics, Industrial Engineering, or related field. A strong
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, tensor analysis, and network science to foster the professional development of team members. Qualifications and experience essential PhD in Applied Mathematics in the fields of Numerical Linear Algebra