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Foundations of Artificial Intelligence Applications should hold a PhD in Computer Science, Electrical and Computer Engineering, Applied Mathematics, or related disciplines and must demonstrate research
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interdisciplinary teams that involve experimentalists and modelers Criteria of the candidates: PhD in Chemical/Mechanical Engineering, Applied Chemistry, Applied Mathematics, Physics, or related disciplines, with
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at conferences and outreach events. Essential qualifications: A PhD (or equivalent) in a quantitative discipline (physics, mathematics, quantitative biology or similar) completed by November 2025 Proficiency in
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inference attacks, to mitigate privacy leaks in MMFM. You will hold a PhD/DPhil (or be near completion) in a relevant discipline such as computer science, data science, statistics or mathematics; expertise in
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-lab.com/ ) • Focus: Structure/function of chromatin-associated complexes using cryo-EM and biochemical approaches • Requirements: PhD in structural biology/protein biochemistry; expertise in protein complex
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PhD in a relevant scientific discipline, for example, Cell Biology-related subject, Tissue Engineering or Biomaterials. Excellent manual dexterity and experience in cell culture and models, and tissue
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environmental trade-offs. Contribute to projects involving capacity expansion, production cost modeling, and equilibrium modeling of power systems. Design and apply mathematical optimization models, including
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plan to use these data to identify the virus and make inferences about potential human infection and transmission. This will involve analysis of viral evolution, simulation of potential scenarios and
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on cutting-edge research at the intersection of statistical modeling, artificial intelligence, and infectious disease epidemiology. This position focuses on developing and applying statistical, mathematical
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management related tasks will also be part of the candidate's responsibilities. Requirements Candidates are required to have a PhD degree in computer science, mathematics, electrical and electronic engineering