We are looking for one postdoc to join the Topological Data Analysis
and Visualization Lab (head by Dr. Bei Wang) at the University of
The Scientific Computing and Imaging (SCI) Institute at the University
of Utah invites applications for one post-doctoral researcher for
interdisciplinary work spanning scientific data visualization and
topological data analysis. The successful candidate will perform a
systematic study of topology-preserving data sketching techniques to
improve visual exploration and understanding of large scientific data.
The postdoc will work closely with SCI Institute researchers and
external collaborators to integrate research into software
applications and apply this software to compelling problems in
scientific applications. The postdoc will benefit from the
interdisciplinary nature of the research that interfaces data
visualization, topological data analysis, and domain science such as
computational fluid dynamics and material science.
As soon as possible, preferably before September 1, 2021.
1) Design, analysis, and application of data sketching techniques.
Focus areas: data sketching (statistical, geometric sketches, graph,
and matrix sketching), data visualization, topological data analysis,
algorithms in machine learning, and data mining.
2) Implementation and evaluation of these methodologies with
open-source software compatible with platforms such as ParaView and
3) Scientific interactions between Utah and other collaborators (at
the University of Utah and national labs).
For more information regarding the project, see
The SCI Institute is seeking a highly talented and committed
individual with a demonstrated ability to work well with minimal
supervision in a multi-disciplinary research environment. Backgrounds
in computer science, data science, applied mathematics, physics, and
computational sciences will be considered. Individuals comfortable
with data visualization, algorithms (in particular, data sketching and
compression), topological data analysis, computational topology,
computational geometry, data mining, and machine learning preferred.
The candidate is expected to be self-motivated and has good
organizational, communication, and teamwork skills.
Required application documents:
– Research statement
– List of two references
Please contact Dr. Bei Wang for further information and send
applications directly to (email@example.com) in addition to
submitting them to the official University of Utah HR site.