[Infovis] Post-doctoral Position in Explainable AI and Visualization at NYU

[Enrico Bertini]

Post-doctoral Position in Explainable AI and Visualization at NYU

The Visualization, Imaging and Data Analysis (VIDA) Center has an opening
for a post-doctoral associate to conduct innovative and exciting research
in the area of explainablity and visualization for machine learning. The
project is in collaboration with Capital One and it aims at developing
novel methods and systems to support model understanding and validation.

The position is available immediately but the start date is flexible.

Required Qualifications:
- PhD in computer science or a related technical field
- Demonstrated ability to work independently and collaboratively in a
diverse interdisciplinary team, and contribute to an active intellectual
environment
- Excellent written and oral communication.
- Proficiency and experience in programming for machine learning and/or
interactive data visualization systems

Expertise in one or more of the following areas is highly desirable:
- Deep learning
- Visualization and interactive user interfaces
- Statistics/probability and machine learning
- Empirical evaluation with user studies

The candidate is expected to:
- Perform excellent scientific research
- Develop research prototypes and conduct on-line and off-line evaluation
- Present results in top-tier international conferences
- Help in guiding PhD and Master students
- Participate in the VIDA activities

To apply, please send a CV and a 1-page cover letter to Enrico Bertini (
enrico.bertini at nyu.edu) and Claudio Silva (csilva at nyu.edu).

About New York University (NYU) and VIDA:

NYU is located in the heart of New York City and is one of the top private
universities in the United States. VIDA is located at the NYU Tandon School
of Engineering in downtown Brooklyn in the Brooklyn Tech Triangle, one of
the most vibrant areas in the city for high-tech industry and education.

VIDA is an interdisciplinary center with strengths in big data and data
science methods, including data management, visualization, machine
learning, and in several application areas such as social sciences, neural
science, medicine, biology, and physics.

The postdoctoral associate will join a dynamic group of undergraduate and
graduate students, faculty members and industry partners to develop cutting
edge research on machine learning visualization and interpretability.
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Enrico Bertini, Associate Professor
Dep. of Computer Science and Engineering
NYU Tandon School of Engineering
2 Metrotech Center, 11201 Brooklyn, NY (10th floor)
Phone: +1 646 997 3731