Assistant/Associate Specialist IN Deep Learning
University of California Berkeley, Electrical Engineering and Computer Sciences
United States


The Electrical Engineering and Computer Sciences Department at University of California, Berkeley is seeking an Assistant/Associate Specialist. Learning a semantic and geometric understanding of the world from visual data is one of the core problems in navigation. We are developing deep learning-based perception-action modules that leverage massive amounts of structured indoor navigation datasets for efficient navigation in unknown indoor environments.


Appointment length:
This is twelve month, 100% time appointment with the possibility of extension being subject to performance and budgetary approval. Anticipated start: September 2019.


The successful candidate’s main duties and responsibilities will be to work with senior PhD candidate to:

  1. Implement deep learning based models for robustly estimating depth, occupancy.
  2. Implement, simulate, evaluate, and run new motion planning strategies.
  3. Work across the software system to define the right data and interfaces for successful motion planning.
  4. Implement real-time tracking, classification, and detection models to equip robots with total scene understanding.
  5. Help to predict trajectories for objects/humans based on semantic understanding of the scene.

Basic Qualifications (at the time of application):
Bachelor’s degree or equivalent international degree


Additional Qualifications (by start date):
Bachelor’s degree or equivalent international degree


Preferred Qualifications:
1) MS in Computer Science or related technical field
2) Experience in designing algorithms for robotic navigation
3) Understanding of state-of-the-art methods for navigation in both the classical and learning-based communities
4) Experience working in Robotics, Computer Vision, Machine Learning, with experience in classical computer vision techniques and graphics pipeline
5) Working proficiency in Python, ideally experience in OpenGL 
6) Strong mathematical fundamentals (linear algebra, optimization, statistics)
7) Knowledge and experience in Deep Learning

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