[Ieee_vis_open_positions] Postdoc and PhD Opportunities on Scientific Data at The Ohio State University

[Guo, Hanqi]

Dr. Hanqi Guo’s group at the Department of Computer Science and Engineering at The Ohio State University is seeking multiple postdoc researchers and PhD students to work with us in cross-cutting areas on scientific data. Our research spans diverse areas involving visualization, data management, and AI. Successful applicants will have opportunities to research cutting-edge problems, engage with a diverse range of real-world applications, and collaborate with leaders in the research field.

Keywords: Scientific data, AI4Science, visualization, lossy compression, topology, data analysis

Requirements for postdoc positions:

  *   PhD in Computer Science and related fields
  *   Background in any related areas: visualization and visual analytics, AI, high-performance computing, computational topology, and graphics
  *   Demonstrated ability to conduct independent research

Requirements for PhD positions:

  *   Bachler’s or Master’s degree in computer science, mathematics, or related fields
  *   Strong problem-solving skills and strong academic/research potential


Highlights of our funded research projects are below.

High-Dimensional Feature Tracking: Computational science, machine learning, and data analysis constantly advance and accelerate scientific discovery but usually depend on parameters that require tuning. A key challenge in such tuning is understanding how a model's outcome changes with varying parameters and the sensitivity of each parameter.  As a generalization of traditional spacetime feature tracking, we research parameter-space feature tracking that associates essential features across multiple data instances to understand the impacts of different input parameters.

Topology-Aware Data Compression: This project focuses on developing topology-aware data compression techniques that preserve critical features in large-scale scientific simulations. The research will enable efficient and effective compression for data-intensive applications in cosmology, climate science, and fusion energy.

Cyberinfrastructure for Lossy Compression Development: This project aims to create a framework for developing specialized lossy compressors for scientific data. By leveraging pre-developed, high-performance data reduction modules and a visual user interface, we will streamline the creation and optimization of compressors tailored to specific use cases.

Visual Analytics of Ensembles with AI: This project addresses the challenges of visual analytics in ensemble simulations, focusing on Earth systems, energy systems, and cosmology. The research will develop AI models, variation models, and actionable visualization techniques to enhance understanding and decision-making in ensemble simulations.


Interested candidates should prepare a curriculum vitae (CV), transcript, and sample publications (if any) and email them to guo.2154 at osu.edu<mailto:guo.2154 at osu.edu>. Please feel free to email me if you have questions.  We are excited to receive your applications.

Best,

--
Hanqi Guo

Associate Professor | Computer Science and Engineering | The Ohio State University
395 Dreese Laboratories, 2015 Neil Ave, Columbus, OH 43210-1210

Computer Scientist (Joint Appointment) | Mathematics and Computer Science | Argonne National Laboratory
Building 240, 9700 S Cass Ave, Lemont, IL 60439

E-mail: guo.2154 at osu.edu<mailto:guo.2154 at osu.edu> | hguo at anl.gov<mailto:hguo at anl.gov>
Phone: 614-247-7848
Web: https://hguo.github.io/

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