VISION & LEARNING FOR AUTONOMOUS AI LAB


LISC

Position

Research Assistant - Monash University
Work type: flexible arrangement (Full time / Part-time / Casual)
Location: flexible and negotiable (preferably working from Melbourne)
Contract length: Up to 24 months
Comment: The positions are available for immediate start. Therefore the applicants may need to be already in Australia or have a valid Australian visa and are willing to travel to Australia immediately.


Position description

We have multiple Research Assistant/Engineer positions in an interdisciplinary project, "Computational Culture Understanding". This project requires a background in one or a few of the following fields: Computer vision, Natural Language Processing, Speech processing and/or Deep learning.
Responsibility:

  • Contribute to the project and help a large team of students and postdocs in both research & development
  • Work on any or a few of the following directions related to the project:
    • Human emotion, body language and action detection & tracking from videos, audio and/or text
    • Human social interaction detection and discovery from videos, audio and/or text
    • Human social-norm detection and discovery
    • Communicative change detection


Skills

We are looking for a highly motivated candidate, who is eager to get involved in many cutting-edge, creative research problems with real-world applications.

Essential Skills:

  • An Honour/Master/PhD degree in Computer Science, Mathematics, Physics, or Engineering.
  • A background in deep learning for computer vision/speech processing/NLP.
  • Proficient programming skills and extensive experience working with one of the main deep Learning libraries (e.g., TensorFlow, PyTorch or Keras).
  • Fluency in written and spoken English, with an ability to communicate scientific ideas to an expert audience, both orally and written.


How to Apply

To apply for the position, please send an email to Dr. Hamid Rezatofighi hamid.rezatofighi@monash.edu, including the following attachments:

  • Full resume/CV
  • Academic transcripts
  • Key selection criteria (skills) response