Connectionists: Research Assistant position in Vision Science at American University, DC

[bei.xiao at gmail.com]

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 seeks a full-time Research Assistant/ Lab
Technician for an NIH-funded project on common mechanisms and individual
variability of human material perception. The main goal is to build
computational models to predict and explain human material perception in
immersive and natural environments. We use a combination of human
psychophysics, deep learning, VR/AR,  and SOTA generative AI techniques to
create immersive environments and measure human material perception with
various tasks.



Job Description

The RA will support research activities in the lab and will work in a
collaborative environment but is also encouraged to pursue research
projects of his/her own. Possible duties include:

   -

   Recruiting human subjects
   -

   Python coding for experiment interface and behavioral data analysis
   -

   Collecting data for psychophysical and EEG experiments
   -

   Building VR/AR experimental interfaces with Unity3D
   -

   Implementing 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 or an industrial research position. The position comes
with a salary and full benefits. Full-time staff at AU can take
undergraduate-level CS courses for tuition remission.  This position is
initially for a one-year contract and can be extended to two years.
Starting date is September 1st, 2023, or soon after.  Please email me if
you have any questions.

Position Requirements:

   -

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

   The candidate should have a strong interest in human behavior and
   fundamental research.
   -

   The candidate should have strong programming skills in Python and is
   familiar with Numpy, Pandas, and other numerical libraries.  Experience
   with statistical methods (linear models, multivariate analysis, etc.).
   -

   Experience with human psychophysics 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
   -

   Material and object perception in infants and children with behavioral
   and EEG methods (collaborating with Dr.Laurie Bayet
   <https://www.american.edu/profiles/faculty/bayet.cfm>).
   -

   Volumetric Capture Studio
   -

   Uncertainty estimation in few-shot learning in text classification
   -

   Prediction of clinical trial outcomes with human experts and machine
   learning models.


The Xiao Lab is located in a state-of-the-art technology building, which is
home to computer science, physics, applied math, and a design and build
lab. The lab has high-performing GPU workstations, haptic phantom devices,
VR headsets, and 3D printers.


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, and the University of Maryland).


How to apply

Please submit your application, including a CV,  and a cover letter
describing your background, experience, and motivation - preferably in PDF
format, and the names of two references that have agreed to be contacted.
Please apply no later than August 15th, 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.       Zhang, X, Lei, S, Alhamadni, A, Chen, F, Xiao, B, and Lu, CT.
(2023) CLUR: Uncertainty Estimation for Few-Shot Text Classification with
Contrastive Learning.  ACM SIGKDD 2023.  PDF upon request.

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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