Connectionists: Job Opening: Full-time Research Assistant in Computational Perception

[bei.xiao at gmail.com]

apologies for cross-listings

*Full-time Research Assistant position in Xiao Lab at American University,
Washington DC.  *

Position Overview



The Xiao Computational Perception Lab
<https://sites.google.com/site/beixiao/> in the Department of Computer
Science at American University is seeking a full-time Research Assistant
(RA) / Lab Programmer for an NIH-funded project on the computational
modeling of human material perception.



Job Description

The RA is to pursue research projects of his/her own as well as provide
support for research carried out in the Xiao lab. Possible duties include:

   -

   Building VR/AR experimental interfaces with Unity3D
   -

   Python coding for behavioral data analysis
   -

   Collecting data for psychophysical experiments
   -

   Training machine learning models


This is an ideal position for someone interested in gaining research
experience in perception science and computational modeling before applying
to graduate school. The position comes with a salary and full benefits.
This position is initially for a one-year contract. Starting date is
September 1st, 2023, or soon after.

Position Requirements:

   -

   The ideal candidate should have a Bachelor's degree in computer science,
   engineering, neuroscience, cognitive science, or a related field.
   -

   The candidate should have strong programming skills in Python and is
   familiar with Numpy, Pandas, Sklearn. Having experience with PyTorch is a
   plus.
   -

   Experience with statistical methods (linear models, multivariate
   analysis, etc.).
   -

   Experience with psychophysics is not required but would be useful.

The Lab and Facility

Xiao Lab studies both human and computer vision with an emphasis on
material perception and recognition. The lab currently has a few ongoing
research projects:



   -

   Learning latent representation of human perception of material
   properties (NIH R15, PI)
   -

   Prediction of clinical trial outcomes with human experts and machine
   learning models  (NSF SBE Core, PI)
   -

   Material and object perception in infants and children  (Internal funded
   by American University, collaborating with Dr.Laurie Bayet
   <https://www.american.edu/profiles/faculty/bayet.cfm>).
   -

   Volumetric Capture Studio (NSF MRI Co-PI)
   -

   Uncertainty estimation in few-shot learning in text classification


The Xiao Lab is located in a state-of-the-art technology building, which is
home to computer science, physics, math, and a design and build lab. The
lab has high-performing GPU workstations, haptic phantom devices, VR
headsets, and 3D printers. We also have access to a new NSF-funded
Volumetric Capture Studio.


Washington, DC, is the US capital and has a vibrant scene of computational
cognition and computer vision research (e.g., NIH, NIST, Johns Hopkins
University, George Washington University, George Mason University, Georgetown
University, and the University of Maryland).


How to apply

Please submit your application, including a CV,  and a cover letter
describing your background, computational skills, experience, and
motivation - preferably in PDF format, and the names of two references that
have agreed to be contacted. Please submit the application no later than July
20th, 2023, to Prof. Bei Xiao at bxiao at american.edu.

Representative Recent Publications：

1. Liao, C, Sawayama, M, Xiao, B.  (2023) Unsupervised learning reveals
interpretable latent representations for translucency perception. PLOS
Computational Biology. Feb 8, 2023. PDF.
<https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1010878>


2. Liao, C, Sawayama, M, Xiao, B.  (2022) Crystal or Jelly? Effect of Color
on the Perception of Translucent Materials with Photographs of Real-world
Objects. Journal of Vision. PDF
<https://jov.arvojournals.org/Article.aspx?articleid=2778489>.

3. He, J. Zhang, X., Shuo L. Wang, S, Huang, Q., Lu, C-T, Xiao, B. (2022)
Semantic Editing On Segmentation Map Via Multi-Expansion Loss. Neurocomputing.
501,306-317. PDF. <https://arxiv.org/abs/2010.08128>

-- 
Bei Xiao, PhD
Associate Professor
Computer Science & Center for Behavioral Neuroscience
American University, Washington DC

Homepage: https://sites.google.com/site/beixiao/
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