A pan-disciplinary academic training for graduate students working on complex systems and data science problems across all fields.
The Ph.D. in Complex Systems and Data Science (CSDS) guides researchers to find, model, understand, and tell the stories about the patterns they uncover. It enables students to build a diverse portfolio of research on important, complex, data-rich problems that matter. Graduate students stand to gain computationally and theoretically rigorous training from this Ph.D. programme, as well as science-wide know-how, encompassing natural, artificial, and sociotechnical systems. This programme resides in the College of Engineering and Mathematical Sciences (CEMS).
Core training encompasses empirical, computational, and theoretical methods for describing and understanding complex systems, thereby enabling students to, where possible, understand, predict, control, and create such systems. Depending on their chosen area of focus, students will work within and across research groups and be immersed in a welcoming and playful scientific community of students through co-location and regular student-led meetings and events.
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