Postdoctoral Research Fellow Position
Starting Date: January 2025 or soon after
Application Deadline: Rolling; applications reviewed starting November 1st, 2024
Location: American University in Washington DC (In-Person, Full-Time)
In-Person Full time
Position Overview
The Xiao Computational Perception Lab in the Department of Computer Science and Center for Behavioral Neuroscience at American University invites applications for a postdoctoral research fellow position, funded by the NIH. This position focuses on understanding the computational and neural mechanisms underlying human perception of materials and objects. This research combines human psychophysics, deep learning, virtual/augmented reality (VR/AR), and state-of-the-art generative AI techniques. These tools are used to create immersive environments for measuring human material perception across various tasks. The start date for the position is flexible, but no later than January 31, 2025. The initial appointment is for one year with the possibility of extension. Salary and benefits will follow the NIH pay scale and will depend on experience.
The postdoc candidate will work with other members in the team including graduate students and undergraduate students. The successful candidate has the opportunity to collaborate with researchers from several institutions, including the University of Giessen, the NIH, University of Rochester, University of Tokyo, and George Mason University.
Key Questions
How does material perception guide action planning in natural tasks?
How is material perception used in reasoning about physics in dynamic scenes?
How do human perception and AI models align?
What are the relationships between vision and language in material perception?
How do humans actively sample image information in material perception across different tasks?
What are the connections between material perception, object recognition, and categorical selectivity?
For more information about the lab, see:
https://sites.google.com/site/beixiao/
Stipend
The successful candidate will receive a stipend commensurate with experience based on the NIH standard.
https://www.training.nih.gov/stipends/
Qualification:
You should have a PhD degree, with training in neuroscience, computer science, psychology, machine vision, cognitive science, or related fields, and success in original research.
Some expected qualifications include:
Research experience in psychophysics
Strong computational modeling skills
Experience in graphics and image analysis
Solid coding skills in Python/Matlab
Being able to Implement and develop state-of-the-art machine learning models.
Strong scientific communication skills
How to apply
Send a cover letter, curriculum vitae, and a description of relevant experience, and arrange for 2-3 letters of recommendation to be sent to bxiao@american.edu.
Representative Recent Publications：
1. Liao, C, Sawayama, M, Xiao, B. (2024) Probing the relationship between vision and language in material perception using psychophysics and unsupervised learning. PLOS Computational Biology. October 3, 2024. PDF.
2. Liao, C, Sawayama, M, Xiao, B. (2023) Unsupervised learning reveals interpretable latent representations for translucency perception. PLOS Computational Biology. Feb 8, 2023. PDF.
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.
Fully-funded PhD fellowship in Neuroscience at American University, Washington DC.
Application deadline: December 1, 2024
The Xiao lab currently has an opening for a NIH-funded PhD fellowship in Neuroscience (Application deadline Dec 1, 2023). The main topic of this PhD studentship is to understand human material perception using deep learning, multi-modal human psychophysics, VR/AR. A parallel goal is to develop algorithms that can simulate, predict and explain human behavior. The candidate also has opportunity to study visual development of material perception through collaborating with Laurie Bayet in psychology to investigate material perception in infancy and early childhood. Xiao lab also collaborates with researchers in Virginia Tech, NIH, and University of Tokoy.
Xiao lab uses a combination of visual psychophysics, computer vision, deep learning, and graphics techniques. Beyond basic human vision research, ongoing projects in the lab includes human-in-the-loop text-to-image manipulation, predicting clinical trial outcome using NLP (NSF funded), uncertainty estimation in text classification with few-shot learning (through collaboration).
Qualification: The ideal candidate should have a Bachelor's degree in computer science, engineering, neuroscience, cognitive science, or a related field.
The candidate will pursue PhD degree in an interdisciplinary brain and cognitive science program. The ideal candidate is expected to have strong technical background and have experience in at least one of the following methods: machine learning, computer vision, image processing, computational neuroscience, human psychophysics, computer graphics, and human cognition. Solid programming skills is a plus. Prospective graduate student should contact me directly and are required to apply to the graduate program Behavior, Cognition, & Neuroscience Graduate Program at AU.
Projects:
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).
Volumetric Capture Studio (NSF MRI Co-PI). This can capture 3D images of moving humans and objects.
Uncertainty estimation in few-shot learning in text classification (collaborating with C.T. Lu at Virginia Tech)
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@american.edu. Bei will also be attending VSS (May 18-22) and SFN conference. Interested candidates can arrange a time to meet the PI.
Applications should be sent apply at BCCN website:
https://www.american.edu/cas/psychology/behavioral/requirements.cfm
More details about Xiao lab: https://sites.google.com/site/beixiao/