|Title: Postdoctoral researcher Zero-Example Deep Learning for Vision||Posted: October 6, 2016|
|Company/Institution: University of Amsterdam|
|Location: Amsterdam (Netherlands)|
|Department: Faculty of Science / Informatics Institute|
Description: The goal of the research position is to study zero-example learning, that is learning without (explicit) visual examples, by using inter-mediate visual representations and reasoning over the visual extend of novel categories. Most current zero-shot prediction systems, use deep convolutional network as feature extractor, yet do not exploit the knowledge encoded in the deep network further. The aim of this project is to devise methods for zero-shot learning directly using transfer within the deep network. The aim is to work on both image classification and video recognition.
PhD in Computer Science, emphasizing computer vision and machine learning;
research record in computer vision, video categorization, zero-shot prediction, semantic embeddings, and/or deep learning is considered a pre;
strong publication record in top-tier international conferences and journals;
solid knowledge of programming (for large-scale processing);
assist in guiding PhD and MSc students working on computer vision topics.
Application Instructions: Please contact me by email (thomas -dot- mensink -dot- uva -dot- nl) with the following attachments:
- a curriculum vitae;
- a research statement (at most 2 pages), explaining your re- search interests and how you think they can be related to the topics mentioned in the Job description above